how to write hypothesis for biology ia

IB Biology Internal Assessment Solved: A Guide to Acing Your Biology IA

What is a Biology IA?

The Biology Internal Assessment (IA) is a take home report on a research question of your choice. It is worth 20% of your final grade and thus it is important to perform well in it. The Biology IA can be daunting. It has a 16-page limit, which might seem like a lot to do, but towards the end of the IA you’ll be wishing you had more pages to work with. This guide is aimed to help you ace the IB Biology IA and to answer any questions you may have.

Choosing a Research Question

The most difficult part of the IA is choosing a research question. There are thousands of topics out there all of which are interesting. However unfortunately when conducting research, you are restricted to scope and the equipment which is available. Well how can you find a topic?

In order to find a topic, I would first choose a syllabus point which sounds appealing to you. Once you have found a syllabus point start googling experiments which have been conducted on that point. They do not have to be identical. DO NOT choose the first experiment you find. I would recommend collecting multiple experiments and read through all of them noting down how it was conducted and whether they had any unanswered questions.

These unanswered questions should be used as motivation when creating a research question. From here you can conduct further research to determine whether it is in the scope or not. If it is then you now have a research question to base your IA off. If it is outside the scope attempt to simplify the question or narrow the focus to that of which you can work with.

Conducting Research

Now that you have your research question it is time to gain background knowledge. Background knowledge is crucial as not only does it enhance your understanding of the topic, but it will be used in your IA to help the reader understand the topic.

When conducting research, the biggest mistake people make is using refutable sources. I would recommend using only published research articles as they have the most evidence to support their claims. This will enhance the reliability of your IA as information you are using is backed up by multiple sources. HOWEVER, it is crucial to ensure that you reference in APA format. We will explore referencing later in the article.

The research you gather should be used in your IA to explain to the reader the reasoning behind your question and to explain any concepts which may be confusing or abstract.

Undergoing the Experiment

Once you have conducted your research you are ready to create your method. The method you create to conduct the experiment is the same method you will place in your report. So, I would recommend that your method is detailed and concise. To ensure this, pretend that you are writing a method to someone who has never conducted an experiment before. This not only makes the method easy to follow for others, but for yourself too, ensuring that the experiment is conducted smoothly.

It is important that you conduct multiple trials. This will be explored in your evaluation as the more trials you conduct the more accurate and reliable your results become. However, when conducting multiple trials, try to conduct them during the same time period as it reduces the number of controlled variables.

Also, keep in mind that there is a possibility that the experiment may not work or that it may have varying results. If that occurs, do not stress, it is completely normal and will give you more to discuss later in the evaluation.

Writing the Report

Now for the fun part. Writing the report. When writing the report there are some sections which are more difficult than others. Below I will explore the sections most students find difficult to complete in a coherent manner.

Background Information

This section involves the most external information. Here you will collate all the information you have gathered on your research question and explore it. One key mistake students make is they do not systematically explore the information. I would recommend inserting subheadings for the various concepts you will explore, ie: 1.1: Photosynthesis, 1.2: electromagnetic spectrum, 1.3 Mentha spicata L, spearmint. Through using subheadings, it becomes easier for the marker to follow the report.

Paraphrase, Paraphrase & Paraphrase. One common mistake students make is that they “dump” information into their report and reference it. AVOID THIS. Instead, I would recommend paraphrasing information, explaining it and its relevance to the report.

Materials, Risks, Environment and Variables

Listing materials is easy and is probably the easiest part of the IA. However, many students do forget to insert the uncertainties for measuring instruments. This is very important as uncertainties must be explored in the weaknesses section for the IA.

Risk assessment should be included in the IA. It ensures that potential hazards which may arise during the experiment have been identified and precautions installed. It also ensures that if someone were to repeat the experiment, they are also aware of the dangers.

The experiments should all be ethical. Hence, environmental considerations should be addressed to show that ethical considerations were taken into account and methods were implemented to ensure the environment was not harmed.

All variables should be discussed in the report. This includes independent, dependent and controlled variables. When listing the variables, it should be discussed how they were controlled and why they should be controlled. This increases personal engagement, as it shows the marker that there was constant reflection being conducted.

Qualitative and Quantitative

When discussing results, both quantitative and qualitative results should be discussed. When discussing quantitative results, I would recommend using tables and graphs. It allows for clear and concise representation of information and allows for easier comparisons and discussions. Averages and standard deviation for the graphs and tables should be explored, as they allow for more accurate and justified conclusions to be drawn. Other tests such as t test, Tukey’s statistical difference test or chi squared test can be used to enhance the IA and discussion of results.

Qualitative analysis consists of differences which can be visually identified. Here you discuss differences in visual representation before the experiment was conducted to after the experiment.

Strength vs Weakness

Strengths: In this section I would recommend listing 2-3 strengths and commenting on how they affected the report or experiment.

Weaknesses: In this section I would recommend listing 5-6 weaknesses, and commenting on how they affected the report or experiment. You should then explore how you can improve this if you were to conduct the experiment again.

Further Questions

At the end of the IA, I would recommend including 2-3 further questions which could be explored if you had the opportunity. This improves personal engagement as it shows the marker that you have reflected on the current experiment and thought about what else you could explore.

Reference List (APA Format)

Ensure all in text references are listed at the end of the IA in APA format and alphabetical order. If this is difficult, I would recommend using the reference tab on a word document. Once you insert the information it converts it to APA format and will list it alphabetically for you.

Remember that the examiners are focusing on the detail of your report and your reflection. If you find that there was an error in the experiment, DISCUSS IT.

Best of luck for the Internal Assessment. You’ve got this!!

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Step by Step Guide to Writing Level 7 IB Biology IA

I. introduction, a. brief overview of ib biology ia.

The IB Biology Internal Assessment (IA) is a crucial component of the International Baccalaureate (IB) Biology curriculum . It serves as a substantial piece of written coursework in the form of a scientific report, focusing on a specific experiment. This undertaking provides students with an opportunity to delve into a topic of personal interest within the realm of biology, conduct experiments, analyze data, and communicate their findings effectively.

B. Importance of Achieving a Level 7

Securing a Level 7 in the IB Biology IA is highly coveted for several reasons. Given that the IB curriculum heavily emphasizes coursework, excelling in IAs can significantly impact your overall grade. Attaining a Level 7 demonstrates a deep understanding of scientific concepts, meticulous experimental design, thorough data analysis, and clear communication skills.

II. Understanding the Assessment Criteria

A. criteria breakdown, 1. personal engagement (2 marks).

Personal engagement involves selecting a topic and experiment that holds personal significance or relevance to the student. While topics often align with IB biology content, students have the flexibility to explore areas beyond the curriculum. Examples may include investigating factors affecting plant growth or studying solubility and diffusion patterns of substances. The key is to explain the relevance of the chosen topic to earn these two marks effortlessly.

2. Exploration (6 marks)

The exploration criterion encompasses providing relevant background information and context for the chosen topic. Thorough research is paramount here, incorporating scientific theory, external references, and IB biology concepts. A well-rounded exploration sets the stage for a robust experiment and hypothesis.

3. Analysis (6 marks)

Analysis begins with formulating a clear research question that includes both the independent and dependent variables. Crafting a hypothesis based on research and scientific theory is crucial. Methodology should be detailed yet accessible, with specific equipment measurements and uncertainty. Data collection, processing, and presentation should be meticulous, with multiple trials for reliability. The evaluation phase involves critical thinking, comparing results to the hypothesis, identifying strengths and weaknesses of the experiment, and reflecting on the process.

4. Communication (6 marks)

Effective communication is essential for conveying scientific theories and experiment findings. Proper formatting, labeling of tables and graphs, and adherence to citation and referencing styles (e.g., MLA or APA) are imperative. A well-structured IA with clear communication enhances readability and comprehension.

III. Final thoughts

In the pursuit of crafting a Level 7 IB Biology IA, don’t hesitate to seek reviews and feedback from your teacher—they’re not only there to guide you but also responsible for evaluating your IA. Their insights can provide invaluable direction, helping you refine your ideas, address any shortcomings, and ultimately enhance the quality of your IA. Additionally, it’s crucial to be mindful of common mistakes such as simple grammatical errors and inadequate labeling of equipment in the methodology section. Maintaining a well-structured layout with clear headers facilitates readability and comprehension, ensuring that your IA is easy to navigate for both you and the examiner.

Remember, the IA is not a task to be completed in a single sitting. Starting early and establishing a brief overview allows ample time for successive rounds of review and editing. By adopting an iterative approach, you can refine your experiment design, enhance your data analysis, and polish your communication. Embracing feedback, avoiding common mistakes, and adopting a diligent, iterative approach are key to achieving success in your IB Biology IA.

Select a topic that interests you personally and has relevance to biology. Consider areas covered in your IB biology coursework but don’t hesitate to explore beyond the curriculum if a particular aspect of biology intrigues you.

Follow a structured format with clear headings and subheadings. Ensure proper labeling of tables and graphs, and adhere to citation and referencing guidelines.

Conduct multiple trials for each experiment to enhance reliability. Use appropriate statistical tools to analyze data and draw meaningful conclusions.

Reflect on possible reasons for the discrepancy, considering experimental limitations and external factors. Compare your findings to existing research and scientific theory to provide context.

Effective communication is essential for conveying your experiment’s findings and scientific concepts. Clear formatting, labeling, and referencing contribute to a well-structured and comprehensible IA.

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May 4, 2022 | IB subjects

how to write hypothesis for biology ia

IA is one of the many things IB students struggle with, but some might feel that writing the IA in Biology is especially confusing since it covers broad topics. This post is for those who are having a hard time coming up with a topic, are worried about writing the IA in Biology overall, or are interested in Biology but not so sure about taking it because of IA. An overview of the subject IB Biology can also be seen in a previous post: Exam Strategy for IB Biology (HL/SL) .

1. Overview of Biology IA

Both HL and SL students are expected to write an IA ( Internal Assessment ) in Biology which accounts for 20% of the final grade . The IA in biology is expected to be a 6-12 pages long report about an investigation a student carries out based on their own hypothesis.

1.1 IA Criteria

HL and SL share the same IA criteria and it’s important to understand the criteria before and while carrying out the investigation for your IA. (Reference: Biology Teacher Support Material )

Criteria Components Assigned Points / Weightings Expected Characteristics
Personal Engagement 2 points / 8%

The evidence of personal engagement with the exploration is clear with significant independent thinking, initiative or creativity.

The justification given for choosing the research question and/or the topic under investigation demonstrates personal significance, interest or curiosity.

There is evidence of personal input and initiative in the designing, implementation or presentation of the investigation.

Exploration 6 points / 25%

The topic of the investigation is identified and a relevant and the fully focused research question is clearly described.

The background information provided for the investigation is entirely appropriate and relevant and enhances the understanding of the context of the investigation.

The methodology of the investigation is highly appropriate to address the research question because it takes into consideration all, or nearly all, of the significant factors that may influence the relevance, reliability and sufficiency of the collected data.

The report shows evidence of full awareness of the significant safety, ethical or environmental issues that are relevant to the methodology of the investigation.

Analysis 6 points / 25%

The report includes sufficient relevant quantitative and qualitative raw data that could support a detailed and valid conclusion to the research question.

Appropriate and sufficient data processing is carried out with the accuracy required to enable a conclusion to the research question to be drawn that is fully consistent with the experimental data.

The report shows evidence of full and appropriate consideration of the impact of measurement uncertainty on the analysis.

The processed data is correctly interpreted so that a completely valid and detailed conclusion to the research question can be deduced.

Evaluation 6 points / 25%

A detailed conclusion is described and justified which is entirely relevant to the research question and fully supported by the data presented.

A conclusion is correctly described and justified through relevant comparison to the accepted scientific context.

Strengths and weaknesses of the investigation, such as limitations of the data and sources of error, are discussed and provide evidence of a clear understanding of the methodological issues involved in establishing the conclusion.

The student has discussed realistic and relevant suggestions for the improvement and extension of the investigation.

Communication 4 points / 17%

The presentation of the investigation is clear. Any errors do not hamper understanding of the focus, process and outcomes.

The report is well structured and clear: the necessary information on focus, process and outcomes is present and presented in a coherent way.

The report is relevant and concise thereby facilitating a ready understanding of the focus, process and outcomes of the investigation.

The use of subject-specific terminology and conventions is appropriate and correct. Any errors do not hamper understanding.

Total 24 points / 100%

2. Examples of Biology IA Topics

Many IB graduates have kindly answered an online survey by MakeSensei and given examples of IA topics in IB Biology. Some of them are RQs (Research Questions), so you might want to see the pattern of how they make RQs for your future IA.

  • What is the effect of exposure to different concentration of sodium chloride solutions for different duration time on the germination percentage, mean germination time, and relative injury rate of Ipomoea aquatica?
  • Lactic acid experiment in milk
  • What is the effect of sodium chloride concentration (0.0, 0.4, 0.8, 1.2, 1.6, and 2.0 %) on the rate of hydrolysis of 1.0 % starch solution by 2.0 % ɑ-amylase (Bacillus subtilis), measured as the rate of decrease in absorbance value (Au s–1), using Spectrophotometer Vis at 434.2nm?
  • Protein-digestive enzyme
  • What is the effect of fertiliser quantity on evening levels of dissolved oxygen in river water samples over a period of two weeks?
  • An Investigation into the Effect of Different Types and Concentrations of Pesticides (Orthoran Acephate, Kadan Safe, Kadan Plus DX) on Seed Germination: Observing Plant Growth of ErucaSativa, Brassica Oleracea, Lepidium Sativum and Perilla Frutescens
  • An investigation into the effect of sodium chloride on plant germination and its growth.
  • (Title: How to make delicious natto) RQ: What is the effect of pre-soaking time of soybeans, 0.00, 3.00, 6.00, 9.00, and 12.00 hours (±0.05 hours), on the length of threads between separated fermented soybeans (natto) measured by a clear plastic ruler (±0.1cm)?
  • Effect of light intensity on the travel activity of a Physella acuta
  • Investigating the effect of concentration of the salt solution on germination and growth of cotton and spinach seeds
  • Investigating the correlation of the length of knee roots of a mangrove and the number of holes crabs make in the given area
  • Effect of temperature on denaturation of albumin protein

3. Tips for Biology IA

3.1 Set Appropriate Independent/Dependent Variables

In order to carry out the investigation with sufficient sample size and trials, there needs to be independent and dependent variables that are both appropriate in terms of the purpose of your investigation. If you want to find out the relationship between X and Y (how X influences Y), then your independent variable should be X and your dependent variable should be Y. Both variables should be measurable , meaning quantitative, to allow various statistical analyses. But having qualitative data is valued in discussion as well.

3.2 The More Data, The Better

It is known that you should have at least 25 samples of data for your Biology IA, but let us explain why. While having multiple trials is necessary for the investigation, each trial should also have multiple samples. Therefore, 5 trials with 5 samples each make up 25 samples in total. Having said that, your sample size is up to you, and having more than 25 samples would only make your data more robust . But make sure you have enough time and energy to process the whole data.

3.3 Use Appropriate Secondary Sources

Doing background research on the field you’re focusing on in IA is required to back up your hypothesis, discussion, and conclusion. A lot of people use secondary sources (sources that are not first-hand) and most often through the internet. But, using Wikipedia or personal blogs would not be appropriate for your IA because they may not be reliable, accurate information. Instead, you might want to use these websites to search for previous academic articles and journals.

  • Google Scholar
  • The World Factbook  (provides you data about the country of your interest)

3.4 Don’t Forget Annotations and Citations

  • Annotations

An annotation is a short comment written near an image to give an explanation. Annotations are necessary when the image and its title don’t give enough explanation to specific objects in the image and your word count is limited. For example, when you’re showing your method with an image of instruments, readers might not understand why you chose those instruments to carry out your experiment. To avoid such inconvenience, annotations provide more detailed information than the title and the main text.

A citation is a short version of the reference to your source and it needs to be in-text or footnote. Every time you mention something that is not original or first-hand, you need to put citation(s) to prove where that statement comes from. If you miss citations, it will be considered plagiarism and you could fail the IB. Therefore, citations are important!! You could use  Citation Machine  to create a reference list and citation for each reference (check which style is preferred by your teacher).

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July 26, 2023

Ace Your Biology IA (HL): A How-to Guide

The Higher Level (HL) Biology Internal Assessment (IA) is a crucial component of the International Baccalaureate (IB) program. It allows students to delve deep into a scientific topic of their choice and showcase their research and analytical skills. In this guide, we will focus on the preliminary pages of the Biology IA, specifically the Title Page and the Content Page, which lay the foundation for a well-structured and successful IA.

Preliminary Pages

Generally, in a HL Biology IA , these pages refer to the Title Page and the Content Page. They come before the actual IA sections and write-up and usually do not require a page number.

Many IB students tend to place these pages on the last of their Biology IA to-do-list. However, we would advice that you do it first.

The Title Page is more than just a formality; it sets the tone for your entire IA. It should contain the following elements:

  • Title (e.g. “A study investigating…”)

A clear and concise title that reflects the essence of your study, such as “A Study Investigating the Impact of X on Y as Shown by…”

  • Research Question

It has to include both the dependent and independent variables.

  • Relevant details such as the scientific name of the organism (if applicable), units, time, and location.

Content Page

The Content Page serves as an organized outline of your IA. It should include the following sections:

  • Title and Research Question
  • Introduction
  • Background Information
  • Variables (Independent, Dependent, Controlled, and Uncontrolled)
  • Preliminary Experiment (with a focus on its relevance to the main experiment)
  • Risk Assessment

Processed Data

  • Analysis (including statistical calculations and graph details)


The IA Title and Research Question  

Identify a broad topic statement, ensuring that your research question is stated and includes both the dependent and independent variables. For example, What is the effect of X on Y as shown by… ? Your research question should include the following, where appropriate:

  • The organism (if appropriate) has a scientific name

Including the following will allow you to effectively convey clarity in your research question , and thoroughly explain what you will be investigating .

Introduction and Background Information 


Your introduction is rooted in background information about the organism and or the topic that you will be investigating in your IA. You should demonstrate strong personal engagement by a statement of purpose.  For instance, you would avoid using cliche phrases such as “I have always loved..”, but rather opt for phrases that clearly illustrate your passion with the real, outside world, or your genuine reason for choosing the topic that you will be investigating.

Background info: 

Go on to enhance your understanding of your research question while ensuring that your background information is:

  • Within context of the range of independent variables
  • Within context of the dependent variables being used
  • In-text cited, based on the referencing systems used in your school (e.g. Harvard/ MLA referencing) 
  • Supported by a preliminary experiment through the inclusion of a short paragraph about how it was carried out, to show your clarity on how you would conduct your main experiment.

While conducting a preliminary experiment shows great engagement, many students do not do it/are not able to carry one out for various different reasons. If you have not carried out a preliminary experiment, research and describe the following instead :

  • Range and intervals of your independent variables
  • How you will be measuring your dependent variable

Null hypothesis : 

“The null hypothesis is a typical statistical theory which suggests that no statistical relationship and significance exists in a set of given single observed variables, between two sets of observed data and measured phenomena” (“Null Hypothesis – an Overview | ScienceDirect Topics”).

For example,

“There is no statistically significant association between X and Y .”

Alternative hypothesis : 

Your alternative hypothesis is an alternative theory that is suggested with direct polarity to the null hypothesis.

“There is a statistically significant association between X and Y .”

  • Independent, dependent and controlled variables are clearly stated
  • Ensure to have at least 5 intervals and at least 15 repeats for each interval
  • Explain how and why you are using those variables, how certain variables may not be controlled, and how you minimise the effects of these to suit it to your experiment effectively

Ensure that all apparatus, chemicals and solutions are listed and / or shown in a diagram if relevant and all apparatus used are relevant. (Not an obligatory list, can be given in the method)

Preliminary Experiment 

The Preliminary Experiment is often overlooked, but it holds immense value in shaping your main investigation. Students can improve this section by linking it seamlessly to their IA. Describe how the preliminary experiment influenced your methodology, analysis, and decision-making process. If you haven’t conducted a preliminary experiment, research and discuss the range and intervals of your independent variables and the method of measuring the dependent variable.

Your method section demonstrates that you have sufficient data that has been collected, and that you have thoroughly reflected on each method of control.

Ensure to :

  • Outline method in a step by step, list-like format
  • Reflect on every controlled variable in the method while explaining
  • State that you have : “Repeated method ____ for verification” at the end of every section.

Risk assessment to ensure safety

Include a risk assessment of apparatus and chemicals and show awareness of:

  • ethical issues – eg handling of animals
  • environmental issues – eg  impact on field sites

Once you have collected your raw data, the next step is to process and organize it for analysis. The Processed Data section is where you present your data in a structured manner, making it easier for readers to interpret and draw conclusions. Follow these steps to effectively present your Processed Data:

  • Data Organization Begin by organizing your data in a clear and systematic way. You can use tables, charts, or graphs, depending on the type of data you collected. Ensure that each piece of data is properly labeled and includes units, where applicable.
  • Data Manipulation In some cases, you might need to manipulate the data to calculate specific values or derive meaningful insights. Show your calculations and formulas used for any data manipulations, and explain the rationale behind these transformations.
  • Averaging and Standard Deviation When presenting numerical data, consider calculating the averages and standard deviations if relevant. These statistical values provide insights into the central tendency and variability of your data points.

The Analysis section is where you interpret your processed data and draw meaningful conclusions from your findings. To conduct a comprehensive analysis, consider the following steps:

  • Statistical Calculations Based on the nature of your data, choose appropriate statistical calculations to support your analysis. Depending on your research question and data type, you might use measures like mean, median, mode, range, standard deviation, t-test, chi-square test, etc. Mention the statistical methods you used and why they are appropriate for your investigation.
  • Graphs and Visualizations Graphs and visualizations are powerful tools to represent your data visually. Create clear and accurate graphs that effectively illustrate the trends, patterns, and relationships present in your data. Choose appropriate graph types, such as bar graphs, line graphs, scatter plots, or pie charts, based on the variables you are analyzing.
  • Data Interpretation Thoroughly interpret the patterns and trends depicted in your graphs and statistical results. Explain the significance of any relationships observed and how they relate to your research question. Use evidence from your processed data and refer to relevant scientific principles to support your interpretations.

Ensure that your analysis section includes sufficient correlated qualitative and quantitative  observations, anomalies that have been clearly pointed out and explained, statistical tests and graphs that explain the data collected.

The figure below is an example graph taken from a model IA, where the student has clearly presented information in a graph.

In the Evaluation section, critically assess your investigation and methodology. Address strengths and weaknesses, reflect on potential sources of error, and suggest improvements for future studies. Consider the following points for a well-rounded evaluation

  • Methodological Considerations Discuss any limitations or challenges you encountered during your investigation. Analyze how these factors might have influenced your results and propose ways to mitigate potential errors.
  • Reliability and Validity Reflect on the reliability and validity of your data and methods. Identify factors that could have impacted the accuracy and generalizability of your findings.
  • Sources of Error Be honest about any sources of error that might have affected your results. Consider experimental errors, sample size, or unexpected external factors that could have influenced your outcomes.

Evaluation : 

  • Conclude by making explicit reference to the research question. In other words, your conclusion should directly answer the question : “Does the data answer the Research Question?”
  • State if your null hypothesis is accepted or rejected
  • Refer to the graph and data points to clearly demonstrate your understanding and strong conclusion
  • Compare the conclusion with published data and predictions 

( A good tip here is to put your graph in and next to it put a graph from a textbook or website. Can you either explain any differences or relate it to scientific theory?) 

  • Strengths and weaknesses of your investigation
  • Further extensions that could have been carried out. 

Figure 1 : Model student IA graph 

how to write hypothesis for biology ia

The Conclusion section is where you summarize your key findings and directly address your research question. Follow these steps for an effective conclusion:

  • Restate the Research Question Begin by restating your research question to remind readers of the central focus of your investigation.
  • Answer the Research Question Clearly state whether your research question was supported or rejected by the evidence presented in your analysis. Use your processed data, statistical calculations, and graphs to support your conclusion.
  • Relate to Scientific Theory Connect your findings to established scientific principles or theories. Discuss how your results align with existing knowledge in the field of biology.

Finally, provide a comprehensive list of all the sources you used in your research. Include academic papers, textbooks, websites, and any other references you consulted. Use the appropriate citation style, such as Harvard or MLA, as required by your school or institution.

Sample IA marked and annotated :

If in doubt, reach out to experienced tutors at Quintessential Education for extra help and guidance. Start your journey towards academic success today!

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A collection of tips and notes for the International Baccalaureate.

IB Biology Internal Assessment (23/24)

Below I will attach a PDF of my Biology IA (submitted for Biology HL). It scored 23/24 (which, according to the boundaries of the M20 session, was a 7). Unfortunately, I don’t know where I lost the one mark.

Quick disclaimer; my Biology IA was a database IA, so the majority of the tips I’ll share in this post will specifically relate to writing a successful database IA. If you’re looking for tips for an experiment-based IA, I’d recommend you go check my post about my Chemistry IA , where I share some of my experiences with an experiment-based IA as well as a general structure I’d replicate when writing an experiment-based IA.

Across my three sciences (Biology HL, Chemistry HL, Physics SL), I wrote two experiment-based IAs and one database IA. As such, I feel as though I have a pretty solid understanding of the pros and cons of each IA “type” (excluding, of course, a simulation-based IA). In short, I can express the essence of these two IA types in quite a rudimentary table:

Experiment-based IADatabase IA
Time and EffortLaboriousMinimal
Analysis and EvaluationStraightforwardIntense

As per the above table, one of the downsides of an experiment-based IA is the amount of effort required to complete it. In experiment-based IAs, a lot of time and effort goes into planning your methodology, conducting preliminary trials, conducting the experiment itself etc. However, this hard work has a payoff, given that an advantage of an experiment-based IA is that the analysis and evaluation of your data is pretty straightforward, since there’s so much you could talk about when it comes to the accuracy and precision of your experiment.

On the other hand, a database IA requires a considerably smaller amount of time and effort to plan. Once you find a good data source and set up your primary equations on a spreadsheet, Excel practically does the rest of the work for you. It personally took me about 2 days to find all my data and process it. However, the drawback to a database IA is that it requires a lot of critical thinking and understanding of statistics and data sampling when it comes to the analysis and evaluation (which contribute half of the points you could achieve for your IA). Ultimately, because most people don’t have a good enough understanding of statistics and data sampling, they tend to score poorly in database IAs or shy away from them completely to begin with. In this post, I hope to provide you with a solid understanding of how to successfully complete a database IA, and hopefully my own IA acts as a decent exemplar for all of you to use.

The IA which I wrote was a “correlation-based IA”, which essentially means it explored the correlation between two (biology) related variables. I have not yet seen someone write a database IA that wasn’t correlation-based, so in this post I’ll be focusing on the structure and content of a correlation-based database IA. To do this, I’ll propose a general structure to use when writing a correlation-based database IA, and expand on some of the technical information that you should include in each section.

1. Research Question:  In this section, state your research question. If you’re writing a correlation-based database IA, you want to make sure that your research question isn’t too simple, and that you add some unique ‘twist’ to your investigation. For example, instead of just determining the correlation between HDI and mortality rates due to CHD, I decided to specifically look at the distinction between this correlation in developing and developed countries. Some other ‘twists’ you could add to your investigation is to look at your correlation in different age groups, or between men and women.

2. Introduction:  In this section, introduce why you ended up choosing to explore your particular research question. This is where I’d sneak in a bit about the connect between the research question and your interests/personal life (I was personally inspired to write my IA after I shadowed a cardiologist at a local hospital). You might also want to mention how answering your research question has important applications in the real world. In my own IA, I made the ‘Introduction’ section part of the ‘Background Information’ section to make sure my IA didn’t exceed the 12 page limit, but if you’re not running out of space I’d recommend making two separate sections.

3. Background Information:  In this section, you want to illustrate all the biology knowledge that’s pertinent to your research question. This section is very important in a correlation-based database IA given that it’s one of the only sections where you’re provided an opportunity to discuss the biological background of your investigation. This section also acts as a reminder that your IA is biology-focused, not maths-focused. Additionally, in this section you should discuss other important background information that’s relevant to your investigation. For example, if you’re exploring the correlation between HDI and CHD mortality (as I have done), you’ll want to use the ‘Background Information” section to not only explain the pathogenesis of CHD but also the significance of CHD as a socioeconomic indicator.

4. Hypothesis: This section is pretty self-explanatory; just state your hypothesis. This should ideally be accompanied by a scientific explanation to support your hypothesis. In my case, I referenced a study about the correlation between the HDI and healthcare quality in a country to justify why HDI and CHD mortality should be negatively correlated.

5. Approach to the Research Question: In this section you should illustrate some of your personal engagement with the IA by explaining how you developed your methodology. For a correlation-based database IA, I suggest that three main points should be considered in this section: 1) how you will control confounding variables in your investigation, 2) how you minimised the effects of errors and variability in your data and, 3) how you standardised your variables. Below I further elaborate on these 3 points, using what I hope is a useful analogy.

In its most basic form, a correlation-based database IA is the development of an algorithm to process raw data into a form which allows you to determine whether a correlation exists between two variables. You can think of this algorithm like a machine, where your raw data is the input and the processed data is the output. In the “Approach to the Research Question” section, you essentially outline the three main ‘steps’ of the machine. The diagram below is a helpful guide:

how to write hypothesis for biology ia

As you see, the first “step” in the database machine is to control the raw data you collect for confounding variables. A confounding variable is a variable that influences both you dependent and independent variable (e.g. a variable that influences both HDI and mortality rates due to CHD). As such, if confounding variables are not controlled for it could lead to spurious correlations in your investigation. Confounding variables can also be variables other than your independent variable that influences your dependent variable, which you should also control (these types of variables are analogous to controlled variables in experiment-based IAs). For instance, lifestyle habits are an example of a variable which may affect both the HDI of a country and the mortality rate due to CHD. Ultimately, to control confounding variables in your experiment you must develop an inclusion criteria. The “Inclusion Criteria” section comes up later in the IA but you can foreshadow its existence in this section already.

The second “step” in the database machine is to take the data you’ve adjusted for confounding and further adjust it, this time for random variability. Random variability in data may be caused for a variety of reasons, and typically these reasons are difficult to identify. However, the existence of random errors in your data may contribute to a spurious correlation, and therefore random variability in data must be accounted for. For example, in my IA I looked at data relating to CHD mortality across different years in different countries. At any one year, there might have been some unknown factor which influenced the CHD mortality in a given country. This factor could be, for example, a sampling error or the introduction of a new procedure to treat CHD. As such, I decided to account for random variability by calculating the mean mortality rate due to CHD.

The last “step” in the database machine is to take the data you’ve adjusted (for confounding and random variability) and standardise it. Standardising data allows you to fairly compare it. For example, in my IA I looked at mortality rates due to CHD, and decided to standardise the mortality rate which I collected by expressing it per 100,000 people in a country’s population. This is important, given that the number of people who die from CHD in any given country is relative to that country’s population. There are, of course, many other ways to standardize data, but for most correlation-based database IAs which I’ve seen (where mortality/survival rates are used), expressing your data per the population is a good way to go.

6. Data sources : In this section of your IA, you should list all of the data sources which you’ve used to carry out your investigation. You should also provide an explanation as to how your chosen data sources are reliable and credible. Generally, if your data sources are well-recognised data-collecting institutions (e.g. the WHO, the World Bank), you can argue that they are also trustworthy and ergo reliable. For population statistics I’d use the World Bank database , mortality rates due to a variety of different diseases are provided by the WHO , and HDI data can be found online on United Nations Development Programme’s website.

7. Variables : In this section, state the final variables which you will explore in the investigation. This includes your independent variable (e.g. HDI) and your dependent variable (e.g. mortality rates due to CHD per 100,00 people). Additionally, state that other variables exist which you need to control (e.g. confounding variables), and that you will design an inclusion criteria in your investigation to control these variables.

8. Inclusion Criteria: In this section you will outline the inclusion criteria which you’ve designed for your investigation. In short, inclusion criteria are characteristics which the raw data you use must have in order to be used in the investigation. These criteria don’t only aim to adjust your data for confounding, but also to control other factors to ensure your results are more accurate and representative. As an example, the inclusion criteria for my own IA were as follows:

how to write hypothesis for biology ia

As you can see, my inclusion criteria consisted of four variables; location, population, HDI, and socioeconomic organisation, which were presented in a table. Given that my investigation looked at the distinction between developing and developed countries, I created separate inclusion criteria for each. For each inclusion criteria which you design, you need to provide an explanation for how it will enhance the accuracy or representativeness of your results. Below I outline the reason for choosing each of my variables. In your own IA, you should also provide a justification for the inclusion criteria you design.

Location : I chose to limit my chosen countries to European countries in order to limit the effects of confounding variables such as lifestyle and dietary habits. These European countries were those defined by the World Health Organidation, as per their website.This inclusion criteria was the same for both developing and developed countries.

Population : If you are sampling data from individual countries, it is necessary to ensure that the population size of these countries is sufficiently large. The larger the population, the more price and representative your results will be (and vice versa). Naturally, I’m not knowledgeable enough to decide which population size is sufficiently large to have confidence in the precision of my data. As such, I referenced a scientific study by Zhu et al. which stated that a sample size of 2 million is enough to ensure the precision of my data. This inclusion criteria excluded certain European countries, such as Liechtenstein and Monaco, from being included in my investigation.

HDI: According to the United Nations Development Programme, “countries with an HDI score higher than 0.788 are considered to be developed, while countries with an HDI value lower than 0.788 are considered to be developing”. I used this parameter to determine which sampled countries are developing and which are developed.

Socioeconomic organisation: I chose to further limit the eligible countries in my investigation to two socioeconomic organisations in order to limit the effects of confounding variables such as economic and cultural status. The two socioeconomic organisations which I chose were the CEIT (Countries with Economies in Transition) for developing countries and the OECD (Organisation for Economics Co-operation and Development) for developed countries.

As you can see, my inclusion criteria specified that variables such as population and HDI needed to be relevant as of 2000; meaning that an eligible developing country had to have, for example; a HDI smaller than 0.788 since the year 2000. This is because I sampled data from my investigation from the year 2000 onwards (given that this was the scope of raw data which I was able to find). Depending on the time period from which you sample your raw data from, this year would likely be different.

9. Safety, Environmental and Ethical Considerations: In this section, briefly outline which safety, environmental, and ethical precautions are necessary when conducting the experiment. Given the nature of a database IAs, there are no substantial safety and environmental considerations to be made. However, you may want to note that it is necessary to use data ethically and in accordance to guidelines set by your database sources (e.g. abide by copyright laws).

10. Methodology and Trial Investigation: In this section you should conduct a trial investigation to gain insight into the feasibility of the correlation you’re investigating, thus providing a justification for you to proceed and carry out the final investigation. Additionally, I would recommend using the trial investigation to explain the methodology you’ve designed for your IA. This will not only allow you to gain points in the ‘Analysis’ and ‘Communication’ criteria of the IA, but it will also save you space given that you will only need to provide the final results of your investigation later on, seeing as you’ve already explained your methodology beforehand.

In order to carry out a trial investigation, it is necessary to randomly sample your data to ensure that your trial investigation is truly representative of the rest of your data. For my IA, I randomly sampled 5 developing and 5 developed countries and carried out the investigation with their data. The way in which you randomly sample your data will vary per IA. Hereafter, explain your investigation’s methodology and all the different tables and calculation which you’ve used.  For every calculation you make in the processing of your data, make sure to include a sample calculation. After processing all of your data and presenting it in a graph, determine which correlation exists in your data and justify why you should go ahead and conduct your final investigation. In my case, I used the R 2 values from my graphs to superficially assess how strong my correlations were, and thus whether I should continue with my final investigation.

(For those of you who don’t know, the R 2 value on a graph represents the proportion of the variance in the dependent variable that is predictable from the independent variable or, in layman terms, the degree of scattering of your data around the fitter trendline. The greater the R 2 value for a graph, the less scattering there is around the trendline, which may suggest a stronger correlation.)

11. Investigation and Results: Given that you’ve already explained your methodology in the previous section of your IA, all you need to do in this section is present the final processed data as well as any final graphs or tables you’ve created. Make sure to state in this section that you utilised the same methodology shown in the trial investigation to conduct the final one. Additionally, you may want to state that the raw data for the final investigation is “available upon request”, just to indicate to the person reading your IA that you actually processed the data yourself.

12. Statistical Testing: This section is, in my opinion, the one where most students miss out on marks for the ‘Evaluation’ criterion of the IA. In a correlation-based database IA, this section is where most students will conduct a statistical test to determine the strength of their correlation. Below I will provide a short description of how to conduct statistical testing for a correlation-based database IA:

Firstly, you need to determine which statistical test you will conduct. The two most frequently used statistical test for correlation are the Pearson’s correlation and Spearman’s correlation. The Pearson’s correlation tests for linear relationships, whereas the Spearman’s correlation tests for monotonic relationships. The difference between these two types of correlations is illustrated in the graphs below:

how to write hypothesis for biology ia

As you see, a linear relationship is a “straight-line” relationship between two variables, whereas a monotonic relationship is one where the function either always increases or always decreases, not both. Evidently, all linear relationships are monotonic, but not all monotonic relationships are linear. However, it will most probably not be clear whether the processed data in your investigation represents a linear relationship or one that is only monotonic. However, in order to conduct a Pearson’s correlation your data needs to meet certain assumptions, one of which is that your data is normally distributed, given that the test is sensitive to outliers and skewness in the data. As such, if you determine that your data is normally distributed, you should conduct a Pearson’s correlation. If your data is not normally distributed you won’t be able to conduct a Pearson’s correlation and should instead conduct a Spearman’s correlation.

An easy way to test whether your processed data is normally distributed, and thus whether you should conduct a Pearson’s correlation or not, is to conduct a skewness analysis. A skewness analysis is a quick calculation which tells you whether or not you data warrants concern of skewness. In a skewness analysis, you need to determine the value of two variables; the “skewness coefficient” and the “standard error”. Both of these variables can be calculated on Microsoft Excel.

The skewness coefficient is a variable which expresses how skewed your data is, and is a separate value for your independent and dependent variable data. Let’s say you want to calculate the skewness coefficient of your independent variable data. First, paste your data into a column on an Excel sheet. If your data spans from, say, cell E8 to cell E28, type the following equation into Excel in order to calculate the skewness coefficient of your data:

Use the same equation to calculate the skewness coefficient of your dependent variable data.

The standard error is different to the skewness coefficient and is usually the same value for both your independent and dependent variable data. The value of the standard error of your data depends on how many data points each of your variables has. In my investigation I had 31 pairs of data points, and therefore each of my variables (independent and dependent) had 31 data points. The value of the standard error was, therefore, the same for both the independent and dependent variable data. To calculate the standard error of your own data, use the following equation on Excel, where ‘N’ is the number of data points you have:

Finally, in order to assess the skewness of your data, you need to compare the absolute value of the skewness coefficient for each of your variables with twice the value of the standard error. If the value for the skewness coefficient is less than twice its standard error, then there is no concern of skewness in the data and the Pearson’s correlation can be conducted. If the value of the skewness coefficient is greater than twice its standard error, then there is concern of skewness and you need to conduct the Spearman’s correlation.

In short, the results of a skewness analysis can be presented in a table, as follows:

how to write hypothesis for biology ia

After the skewness analysis you need to conduct your chosen statistical test. I personally conducted the Pearson’s correlation, but I will demonstrate how to conduct both the Pearson’s and Spearman’s correlation below:

Pearson’s correlation: The Pearson’s correlation tests the strength of a linear correlation. The result of the Pearson’s correlation; the Pearson correlation coefficient ( r ), expresses the strength of and direction of a linear correlation (ranging from -1 to 1). The Pearson’s correlation is conducted using the following formula, where r is the Pearson correlation coefficient, x is your independent variable data, y is your dependent variable data, and n is the number of data pairs in your investigation.

how to write hypothesis for biology ia

As illustrated by the above equation, it is necessary to determine the sum of   x, y, xy, x 2 and y 2 . After doing so, plug in your results into the above equation (alongside the value for n ), and the result will be your Pearson correlation coefficient.

Spearman’s correlation: Conducting the Spearman’s correlation is slightly more complex than the Pearson’s correlation. Similarly to the Pearson’s correlation coefficient, the Spearman’s correlation coefficient expresses the strength of and direction of a linear correlation (ranging from -1 to 1). Given that I haven’t personally conducted the Spearman’s correlation for my IA, I’m not very experienced in the process of doing so, but I found a great link which is very clear at describing how to calculate the Spearman’s correlation, which I will link here .

Lastly, after conducting the statistical test of choice, you need to ensure that the results of your statistical test are “statistically significant”; that is to say that the correlation which you’ve determined using the statistical test is caused by something other than chance. To determine statistical significance, you need to compare the result of your statistical test to a certain “critical value” which is based on the degrees of freedom and level of confidence assumed. I defined the two latter terms below:

  • degrees of freedom : the number of values in the final calculation of a statistic that are free to vary. The degrees of freedom for an investigation is calculated as the number of data pairs minus 2 (e.g. for my investigation, which had 31 data pairs, there would be 29 degrees of freedom)
  • level of confidence : the level of confidence when determining statistical significance refers to the risk that the correlation investigated is due to chance. Typically, a level of confidence of 0.05 is chosen, which denotes a 5% risk that the correlation investigated is due to chance.

You can determine the critical value for your investigation using either this document for the Pearson’s correlation or this document for the Spearman’s correlation. For instance, if you conducted a Pearson’s correlation and had 10 degrees of freedom at a level of confidence of 0.05, your critical value would be 0.576 (with reference to the appropriate document). Ultimately, if the absolute value of the correlation coefficient you have determined is greater than your assigned critical value, the results of your statistical testing are statistically significant, and vice versa.

I know this section was long, but it’s really important to get this part of the IA right in order to score highly. Remember, the statistical testing has three main parts: 1) conduct a skewness analysis to determine which statistical test to conduct, 2) conduct your chosen statistical test and, 3) determine if the results of your statistical test are statistically significant.

13. Analysis and Conclusion : In this section, analyze your final, processed data and provide an answer to your research question (if possible). This section should summarize the data which you’ve collected and how it (hopefully) supports your initial hypothesis. When analyzing the data, take into account the results of your statistical testing as well as the R 2 values from your final graphs.

14. Evaluation of Errors and Improvements: This section is of paramount important to the overall quality of your IA. The more detailed and thoughtful your evaluation of your investigation is, the better. To begin your evaluation, start by pointing out some of the strengths of your investigation. This could be the use of a trial investigation, or the thoroughness of your statistical testing. However, the bulk of the ‘Evaluation’ section should focus on identifying errors in your investigation and suggesting possible improvements to them. I mainly focused on how my methodology failed to take into account certain confounding variables, given that I suggested that these confounding variables were what caused my final correlations to be less than perfect. As such, most of the major errors in my investigation were linked to the nature of my inclusion criteria. Additionally, you may wish to point out some methodological errors in your investigation, such as the way in which you standardised your data, or how you could enhance the precision of your results by reducing the effects of certain random errors.

15. Extensions: In this section, identify any possible extensions to your investigation. It’s important to differentiate between improvements in the previous section and extensions in this one. An improvement involves tweaking your current methodology to ensure a more accurate and precise investigation. An extension, on the other hand, is suggesting an entirely new part of the methodology that would explore another aspect of your investigation. The extension you identify should, however, still be aimed at exploring something in the domain of your research question.

16. Literature: This is the last section of your IA and should include all of the sources which you’ve used, referenced in whichever style you want (I chose Chicago-style citation). Make sure to also reference any images which you’ve included in your IA in this section as well.

I hope this information is useful, and good luck!

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12 thoughts on “ ib biology internal assessment (23/24) ”.

Thank you so much for this!!! You probably saved my ass, bc I had to write a second biology IA (the first was was too shitty). This is such a good guide, thanks again!!

You don’t know how thankful i am for this like you saved my ass but i still need more helppppppp! My ANOVA test isnt’t working and my R values aren’t matching my data. Please help

Hi! Thank you for the post, it was really helpful. I was just wondering what font, font size and margin size you used? Also, I’m still not sure if the bibliography counts in the page limit but, correct me if I’m wrong, it didn’t seem to count in your IA?

Hi! I’m glad you found the post useful. I used Times New Roman size 11. I’m not really sure what margin size I used – I basically stretched the margins as far as I could because I had quite a lot of words to fit into the 12-page limit. To my knowledge, the bibliography does not count as part of the page limit. All the best!

Thank you so much for replying! The info was really useful 🙂

Hi! I was wondering how exactly you were able to gather your data from these databases? The websites are quite confusing

Hi! You usually need to download an Excel sheet or look through large tables to gather data from databases. For the WHO database, for instance, you can download different Excel sheets depending on what type of data you’re looking for. Hope that helps!

Hello. I just wanted to thank you for your precious advices. They are coming in really handy since I am taking HL biology too.

Hi! I was feeling so stressed because i didnt knew what to do with my ia and this helped a lot. Thank you so much!

Hi. Just wanted to thank you for the useful tips. They really helped me out when writing my database IA

Damn, I find myself on this website a few days before Christmas as the only one from my school doing a DB IA and I gotta admit I was super lost until I found your step-by-step guide Thank you very much.

you might just be the greatest of all time

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IB Better

50 IB Biology IA Ideas

how to write hypothesis for biology ia

Abiotic factors on the Biodiversity in a habitat

Different abiotic factors affect the growth of different plants, test the different conditions and then note how plant species change in their presence.

Experimental setup:  In this ecological experiment, you will use quadrat sampling to test how successfully different plant species grow in environments. Read more about quadrat sampling here

Independent Variable: Soil pH, Nitrates in Soil, Oxygen concentration

Dependent Variable: Presence or absence of certain species

Challenges: Providing biological context for why you’re measuring certain factors.

Stomatal Density in Different Conditions

Stomata are the areas of gas exchange in leaves. Different plants that live in different conditions will have different requirements for gas exchange.

Experimental Setup: F ocus on how leaves in different conditions vary in their stomatal density. Test the stomatal density of different leaves exposed to variable conditions using a microscope.

Independent Variable: Light exposure, Different Species, Atmospheric CO2 concentration

Dependent Variable: Stomatal density (seen under the microscope)

Challenges : mathematical analysis

Comparing different plant species transpiration rate changes in response to stimuli

Different plants will change their transpiration rates in response to the environment. Investigate how different species of plants respond differently to environmental stimuli.

Experimental setup:  Use a potometer to measure the rate of transpiration. Change the different conditions in which the plants are found as well as the species.

Independent Variable: Plant species + humidity/temperature/ light intensity

Dependent Variable: Rate of transpiration

Whats next?

We hope our list of Internal Assessment Ideas was useful.

If you’re looking for guidance on how to actually write an IA once you’ve chosen your topic, check out our IA Checklist post!

If you’re struggling with the Paper 2 Data Based Questions, we also have a post about that here .


Top 80 Most Common IB Biology Exam Questions

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IBDP Biology

Internal assessment (ia) tips.

“Think about your method like a recipe. It should be easy to follow.” Author: Matthew Bowen Trained in the UK by PGCE following a degree in Biochemistry and Microbiology with over 10 years of qualified teaching experience. IB Examiner for over 5 years.

Navigate the IB Biology IA Tips easily by clicking the section icons below.

Personal Engagement

Exploration, communication, requirements of internal assessment (ia).

The internal assessment (IA) for Biology is a scientific report which explores a research question (RQ) written by the student. The requirements for the IA are the same regardless if you are studying at standard or higher level and is worth 20% of the final grade in both cases. In total the IA is marked out of 24. The breakdown is shown below along with tips and points for consideration for each of the criteria areas.

Important: Visit the official IBO page for the most updated information about this subject.

[2 marks, 8%]

A rationale developed in the exploration is good and supports the justification. the danger is personal engagement can be presented as a separate section which is a waste of time and space and is irrelevant..

Many candidates write this as a separate section, but it really does not need to be. It is marked on the essay as a whole not based upon an invented story. The examiner is unlikely to believe if your IA is sent off as as part of the sample. It is better to use this valuable space to instead focus on the report. Personal engagement may sometimes be reflected as your rationale or how you have designed the experiment. The danger is personal engagement can be presented as a separate section which is a waste of time and space as it is irrelevant.

[6 marks, 25%]

A good method can be followed from start to finish simply and result in similar outcomes to those that you obtained when doing it. Make sure you also plan to collect qualitative data as well as quantitative.

Setting out a clear and well thought through research question is vital for setting the entire report. State the research question (RQ) early and justify why it is suitable.

Use plenty of sources in writing your background information and refer back to them later when supporting any conclusions you draw. These sources can be textbooks, journals, websites, interviews etc. Ensure that they are properly referenced according to which ever referencing system you are using. This is not stipulated by the IB as they just state a system is used consistently, but most schools will have one they follow and insist you use. If you have a librarian, they can be invaluable in supporting you to reference correctly.

Always avoid the word amount . It is a vague word with little place in scientific writing. Be more specific, use words such as volume or mass in place of amount.

Think about your method like a recipe. It should be easy to follow. Hence numbered steps, all values for measurements and pieces of equipment are clearly stated to the reader. For example, if baking the first couple of steps may read:

  • Weigh out 200g of plain flour using a scale. Add into a bowl.
  • Add 200ml of milk measured using a 1000ml measuring jug.

There must be consideration of safety, ethical and environmental issues. All three of these must be shown to have been explored. This may just be that it is stated there are no major issues, this still shows these areas have been considered to fulfil the criteria. Remember a hazard is what could cause a problem and the risk is the probability of that happening. Do not confuse the two. If you do any sort of microbiological investigation the risk assessment will need to be carefully carried out and presented.

If you are not proficient in drawing a graph with excel or other graphing software, then it is best to hand draw them on graph paper. This will result in it taking longer to produce but is likely to result in a much clearer graph which includes all the components that would be expected of a high-quality graph. Common errors include issues such as gridlines being too widely spaced, missing axis labels or uncertainties and inappropriate lines to represent trends.

If you are doing calculations, you need not show all of them. One as an example is sufficient. Some calculations such as standard deviation may have been done using excel or other software. In this case the calculation need not be shown but it can be stated they were calculated on excel and the formula provided.

In this section further research should be used to support the explanations given behind conclusions and explore the hypothesis.

Ensure you refer back to your research question and hypothesis in the conclusion. You can not accept a hypothesis only support or reject it. The limited data you have can’t prove anything so as with amount earlier – avoid this word at all costs. If you have done statistics and have a null hypothesis also clearly comment on if this is accepted or rejected.

In this section further research should be used to support the explanations given behind conclusions and explore the hypothesis. Data from other scientific experiments or published theory around the topic will support findings well and link your research to the scientific context.

In concluding also mention any qualitative data you obtained and how it supports your overall conclusions. This is often overlooked.

Do not forget to also include strengths in your evaluation. They are clearly stated in the criteria and thus must be addressed.

It is generally a good point to say that the number of repeats could have been increased to increase reliability. In addition, explore the intervals between values or intervals for your independent variable it often could have been smaller increments.

[4 marks, 17%]

You may find it more suitable to write conclusions after the evaluation have considered what the major areas of weakness were and how this may affect the conclusion that can be drawn..

This certainly should not be a section and is based holistically on the report written. The structuring is a large part of this. The criteria can be easily fulfilled by simply following a structure that cover the areas in the way they are set out by the IA criteria. You may find it more suitable to write conclusions after the evaluation have considered what the major areas of weakness were and how this may affect the conclusion that can be drawn. The IB has not dictated a set structure for this but states that is should be well structured and clear. In the subject guide the section for internal assessment useful for students can be found from pages 154 – 158, with communication being on page 158.

Learn how to subscript and superscript in whatever word processor you use. Symbols such as O 2 and Cu 2+ are often not properly formatted and so do not meet the accepted scientific conventions. The same goes for o C. This often is written as degrees Celsius or even worse as just degrees. This is very poor scientific writing and done repeatedly will result in the loss of communication marks.

Consistency in decimal places is important. All results should be to the same number of decimal places and the mean of them only to one more decimal place if suitable. Whole numbers such as, for example a number of leaves should not have decimal places in the mean but be rounded to the nearest whole number.

The guidance is 6 to 12 pages not including any appendices. This however does not mean that you can just put all tables etc as an appendix. You could run the risk of these being excluded from marking if you do so. Try to be concise in your writing only including relevant information to support the research question you have devised. The 6 to 12 pages does also not mean it can be font size 8. Generally, go for a font size of 11 as suitable size that would be readable for teachers and examiners if your work is included in the sample sent to the IB.

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IB Biology IA Marking Criteria – How To Use It For A Top Score

By TutorsPlus

IB Biology Internal Assessment

As an IB Biology student, you probably already know that your final grade isn’t just based on the final exam. A full 20% comes from your Internal Assessment (IA). Naturally, you want it to be a success, and this is why you need to know your IB Biology IA Marking Criteria.

Have you heard people say “If you don’t know where you are going, how do you know if you get there?” The saying also applies to your Biology IA. If you don’t know what examiners are looking for, you won’t have a chance of getting the highest grade.

We are here to help you with that. At TutorsPlus , we’ve put together a comprehensive guide on the IB Biology Internal Assessment marking scheme (takes effect in 2025) so that you can aim for a top score. 

Biology IA Marking Criteria Overview

Let’s start with the basics. Your IA is marked out of 24 points, spread across the following four criteria:

  • Research Design (6 marks);
  • Data Analysis (6 marks);
  • Conclusion (6 marks);
  • Evaluation (6 marks).

You can learn more about these criteria and the IB Biology IA mark scheme from the official IB Biology guide (the first assessment in 2025).

IB Biology IA Marking Criteria Breakdown

Below, we’ll break the Biology Internal Assessment criteria down one by one.

Research Design

To gain 6 points for Research Design, you need to have a well-thought-out and planned research.

It all starts with a descriptive title that captures the essence of your experiment along with a clear research question. It is also necessary to provide some background about what motivated you to choose this topic. This can be an observation, experience, or story from your life that sparked your interest.

If you struggle to come up with an original research question, we’ve compiled a list of 30+ Biology IA topic ideas .

Besides the question, you need to state your hypothesis and take care to explain how it is grounded in existing research. You need to cite at least 5 sources to back up the rationale for your hypothesis.

For many students, one of the most difficult parts is to explain their experiment methodology. We suggest that you start with an image or diagram of your experimental apparatus and list all equipment and materials you used. This also includes the exact amounts, sizes, models, etc. Then, write out each step of your procedure like you’re giving instructions to another student to replicate your experiment.

It is also essential that your IB Biology Internal Assessment specifies every type of variable – independent, dependent, and controlled. Along with this, you need to provide the exact units of measurement you will use.

Additionally, be sure to note how you controlled variables and made systematic manipulations to isolate your independent and dependent variables. You should conduct at least 5 repeats of your experiment. In the process, carefully describe any errors, discrepancies, or difficulties you encountered. Remember, your examiners require a scientifically rigorous procedure.

If there are any kind of concerns associated with your investigation (environmental, ethical, safety, etc.), explain your attempts to minimise the issues.

Data Analysis

This criterion deals with data collection, procession, visualisation, and interpretation.

To meet this IB Biology IA criterion, you need to introduce the quantitative and qualitative data you’ve collected during experimentation. Start by explaining how this data helps answer your original research question. Then describe how you recorded and processed the obtained data.

Show your workings – all calculations must be mathematically accurate and presented in an organised manner. Don’t forget to include a sample calculation in order to walk an evaluator through your method of data processing step-by-step. Remember, there shouldn’t be major omissions or inaccuracies since they may prevent you from coming to the right conclusion.

Visual representations are vital in Biology IAs as well. That’s why you should include properly labelled graphs, charts, and tables displaying relations between variables. There must be informative titles, axis labels with units, legend if needed, and maximum/minimum values. Also, make sure to visually convey any uncertainties, errors, or anomalies in your data where relevant. You can even provide brief conclusions for such instances.

In this section, you need to interpret your findings. To begin with, refer back to your research question – did your findings align with or contradict it? Make sure to base your conclusion on the data you obtained and analysed.

Also, to get all 6 points for the Conclusion criterion, you should compare your results to the well-established research or experiments, specifically, those published in scientific literature. To do so, you must appropriately cite these materials so that your examiners can trace them. The reference list should include at least 5 relevant sources in alphabetical order, consistently formatted according to the citation style specified by your school.

IB Biology Student Researching IA

This crucial section is where you reflect on your findings.

First of all, you need to speculate thoughtfully on potential reasons why your hypothesis was supported or disproved based on scientific principles. Try to identify limitations, sources of error, and weaknesses in your experimental design and methodology. This could be insufficient precision of measurements, methodological weaknesses, confines of the system, assuming you’ve made, etc.

Whatever the reasons, discuss them and suggest ways to improve your experiment if you had a chance to do it again. And don’t forget to explain how these modifications are able to improve your methodology or experimentation.

Remember, the evaluation criterion is supposed to show the examiners that you can think critically.

The Overall Quality of Your IB Biology Internal Assessment

It goes without saying that your investigation should be easy to understand. That’s why you must break it into logical sections with descriptive headers. Don’t forget to check out our detailed guide on how to write Biology IA , to know more about its design and format.

Be sure to carefully read your Biology IA before you submit it. Although there is no longer a Communication criterion, spelling and grammar mistakes, unclear structure, insufficient or wrong labels, and other avoidable omissions can cost you valuable marks.

Overall, your individual research paper must contain no more than 3,000 words. You should specify the exact word count (excluding the front page, the list of references, and graphs) at the beginning of your report.

IB Biology IA Marking Criteria – If You Need Extra Help to Nail Your IA

There you have it – our comprehensive breakdown of the IB Biology IA marking criteria for a top score!

Needless to say, it is a lot of work to design, conduct, and write up your experiment. Don’t be afraid to get help along the way. Working with an experienced IB Biology tutor is a great way to refine your skills and take your IA to the next level.

A tutor can provide guidance on developing an innovative research question, perfecting your methodology, analysing data effectively, and crafting a logically structured, scientifically accurate paper. At TutorsPlus, we have a team of talented tutors who have supported many students in achieving top Biology Internal Assessment scores. Feel free to contact us – 41 022 731 8148 or [email protected] – if you need that extra boost of expert guidance for your Biology IA success.

how to write hypothesis for biology ia

Sara has been an education consultant for TutorsPlus for 15 years, and is an expert on international IB education.  She is also a parent of two lively children.

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IB Biology IA – Top 5 Tips on How to Get a 7

how to write hypothesis for biology ia

Remember that your grade in Biology is not only down to your final exam. 20% of your overall grade is determined by your Internal Assessment. As such, we want to make sure that you can get the top marks possible in this crucial part of your IB. This isn’t an easy assignment, so our top biology tutors have put together this blog in which we’re going to outline the top 5 tips to ensure that you have all the components of a successful IA! These components are based on the criteria that you’re graded upon.

#1: Personal Engagement

The IA needs to be related to your life. An experiment that lacks any significance to your life, or where you fail to show a reason why the findings can influence your life, will naturally be downgraded. A way to do this is to ensure the research question is relevant to local issues.

Designing a unique experiment and research question. Sure, you can grab a topic from a list of Biology IA topics, but if you don’t then take that and alter it so that it is unique to you, you will definitely lose points to personal engagement!

Get Support from a Top Tutor Today

At Lanterna we have over 300 tutors who smashed Biology. They know exactly how to get an 7 in your Biology IA and can give you tips and tricks on how you can do the same. What are you waiting for? Get your own tutor today!

Get Your Tutor Today

#2: Exploration

A quality research question is essential to a high IB grade. A few tips are that your research question should:

  • Cut to the chase – don’t be too wordy
  • Be self-explanatory – you shouldn’t need another sentence to explain what your research question means
  • Establish a dependent variable
  • Establish an independent variable

In addition to your research question, your variables (independent, dependent, and controlled) must be clearly defined along with a brief description about how each will be measured.

Make sure to establish a hypothesis that is backed by scientific thinking and based upon the predicted relationship between your variables.

#3: Collecting Data

The magic number is 25 – this is the minimum number of samples that must be obtained for your experiment. Why 25? 5 trials for each of the 5 values you’ve chosen for your independent variable. For example, if you are considering what a change in X has on variable Y, you would choose 5 different values of X and record the value of Y at each X through 5 trials!

#4: Conclusion and Evaluation

In your conclusion, make sure to refer back to your original hypothesis. Was it correct? Why or why not? Were there any significant differences from what you expected? If so, what may have caused these differences?

The evaluation is your chance to discuss any limitations in your experiment and potential weaknesses in the methodology you’ve chosen. Can these results be trusted, or is the reliability questionable? We recommend including what you would change if you were to do the experiment again to get greater accuracy or precision of data.

#5: Format Just because it’s a science IA doesn’t mean we can forget about the rules of essay-writing that we’ve learned in other classes. Referencing and citing your sources is just as important in biology as it is in any other subject.

Make sure to use in-text citation in MLA format, and a bibliography at the end of your IA.Just like all official IB submissions, your IA should be typed in a standard 12pt font.

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