reflection essay about statistics and probability

Reflection about Statistics and Probability – Essay Sample [New]

Reflection paper about statistics and probability: introduction, what i learned in statistics and probability, reflection about statistics and probability: data analysis, reflection paper about statistics: future studies, statistics reflection paper: conclusion.

Learning statistics is viewed as an essential subject. It is also crucial to do statistics and probability reflection about their role in math, data management, and one’s daily life as a student. This statistics essay sample is going to cover what I have learned in statistics and probability. Essay will talk about my experience of learning the necessary skills for analyzing data and predicting possible outcomes.

I have extensively studied statistics and probability throughout this course. The probability course appeared to be a useful tool to apply in areas of statistical analysis. However, the part of learning statistics is much more prominent.

Statistical knowledge for both statisticians and non-statisticians is essential (Broers, 2006). So it is recommended that people from all fields be given the necessary statistical skills.

For that kind of reason, to gain quantitative skills to be applied and worked on in many ways, I followed this course. In this regard, I had hoped to acquire knowledge in designing experiments. I had wanted to grow in collecting and analyzing data, interpreting results, and drawing conclusions as well (Broers, 2006). I summarized and analyzed the results in my reflection about statistics and probability.

I can proudly say now that I have learned many useful things. I now understand math applications very clearly. I know how to collect, arrange, and explain the details. In data analysis, I may apply central tendency measurements such as mean, mode, and median.

I may also use dispersion measures to explain the data, such as standard deviation and variance. Furthermore, I have a detailed understanding of probability distribution. I can see what conditions are to be fulfilled for a normal distribution (Broers, 2006).

For example, I am aware of conditional probability and its applications. I also know how to use The Poisson process, Brownian motion process, Stochastic processes, Stationary processes, and Markovian processes. I learned the Ehrenfest model of diffusion, the symmetric random walk, queuing models, insurance risk theory, and Martingale theory.

Now, I can determine the relation between the two data sets. I can distinguish dependent and independent variables as well as the sort of relationship between them. I will tell you whether one random variable is causal to another. I am also able to determine positive, negative, and minimal correlations (Broers, 2006).

In most instances, data collection on an entire population is delicate (Chance, 2002). I got the necessary skills in sampling techniques in this respect. I have the skills to analyze sample data. Now I can draw inferences about the entire population using statistical probabilities and hypothesis testing.

In hypothesis testing, one seeks to determine whether the outcomes of a given sample are due to chance or known cause (Chance, 2002). Knowledge is used in the implementation of significance level, critical value, degrees of freedom, and p-value. One must be able to present the null hypothesis and the alternative hypotheses (Chance, 2002).

Now I’m able to use a t-test to assess if there are statistically significant variations between two data sets. In this regard, I understand the required assumptions for the t-test to be applied. I have a clear insight into the analysis of variance (ANOVA), both single and bidirectional. However, I feel that further practice would improve my knowledge of all of those applications (Chance, 2002).

This program has provided me with a good understanding of how statistics play a major part in life. Among other areas, statistics is the most commonly used research method in medicine, education, psychology, business, and economics (Rumsey, 2002). It helps to shape the choices people make in their everyday lives. Statistical studies may provide a clear picture of the consequences. For example, the results of such activities as smoking and contribute to corrective steps.

I was always keen to build a stable scientific career. I have now decided to major in statistics after taking this course. I would like to have advanced statistical skills that will help me to manage and evaluate complex research problems. The knowledge I’ve already obtained in this case will give me a strong foothold.

The goals I had hoped to accomplish by following this cause were well achieved. Now I can conduct experiments and collect, analyze, and interpret data. In real-life scenarios, I can apply that information and draw conclusions that will help develop answers to some issues.

Also, I have thoroughly studied and understood various causes of probability. I will be able to apply this knowledge where needed. Nevertheless, statistics will remain my main field of research.

This course, therefore, gave me the desire to seek additional statistical knowledge. For this reason, I intend to be in a better position in statistics to deal with more complex research issues.

• Broers, N. J. Learning goals: the primacy of statistical knowledge. 2006, Maastricht: Maastricht University.
• Chance, B. L. Components of statistical thinking and implications for instruction and assessment . 2002, Journal of Statistics Education, 10(3)
• Rumsey, D. J. Statistical literacy as a goal for introductory statistics courses. 2002, Journal of Statistics Education, 10(3)

What should I include in my statistics reflection paper?

Your statistics essay should contain a number of research data. Thoroughly research your subject. You can also include visual support like graphs or diagrams. Make sure the statistics are broken down and provide a general image of the issue.

Why are statistics so difficult?

Much of statistics makes no sense to students as it’s taught out of context. Many people often do not understand anything until they begin to examine data in their studies. You need to gain academic knowledge before you can understand statistics.

How do you start a reflection on statistics?

The good idea is to start your essay on statistics with a choice of the right topic. Make sure to research everything thoroughly and take notes of interesting observations. You should have a detailed understanding of a problem, and work well with data.

What is the aim of statistics?

Statistics aims to help you to use the right methods to gather the data. It ensures you use analysis correctly and present the results effectively. Statistics are essential to make science-based discoveries, make data-based decisions, and predict possible results.

What is the importance of statistics and probability?

Statistics is the mathematics that we use to gather, organize, and interpret numerical information. Probability is the study of possible events. It is often used in the analysis of chance games, genetics, and weather forecasting. A myriad of other everyday occurrences can be examined.

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Importance of Statistics in Daily Life Essay

In order to explore the use of statistics in everyday life, the essay should start with a debatable statement. On a daily basis, people collect and analyze a lot of information presented in numbers, and it is closely associated with different aspects of their lives. Thus, it is typical to apply the elementary statistical approaches to examining the learned material about everyday activities. It can help to get the average results in relation to actual events or phenomena.

However, many people do not guess that they use such principles as the base for their knowledge. So, to reveal the importance of statistics in daily life, this essay will provide different real-life examples and explain the application of various data analysis methods.

Moreover, when persons have to present the solution to this or that question or decide how to act in the definite situation they also use the statistical data on the issue as one of the main arguments which can influence the further development of the case. That is why statistics can be defined as the science which deals with the data’s collection and its interpretation according to the certain task, and the results of the research can be effectively used in many spheres. From this point, the relative value of statistics for the everyday life is in the fact that people have the opportunity to plan their actions according to the statistical data with references to those results which can satisfy or not their expectations.

People are usually interested in the average temperature and the weather forecasts, in the amount of people who prefer this or that product which they usually purchase. These persons listen to the economical news in which the data of statistics on the state’s development are presented and pay attention to the risks of the transport incidents before going out the house. The statistical data influence all the aspects of the people’s life during the whole day.

When an individual wants to learn about the latest news he concentrates on the information which is interesting for him personally, and these facts are often given in the form of numbers. The average results in different fields and areas from the average level of incomes in the country and the average level of attendance the local library till the average data on the consumers’ preference of brands and services can provide the basics for the people’s choices and usual decisions which are made as a part of the daily rituals and routines.

One more effective advantage of statistics is the possibility to offer the prognoses of the development of definite situations and processes. People are inclined to use the statistical prognoses when they plan such significant changes in their life as the search of the new job, new investments in companies, travelling, and long-term projects. Statistics as the science is based on the strict mathematical calculations and formulas (Bluman, 2009). That is why its methods can be discussed as the effective ways of interpreting the collected quantitative information on any aspect of the life.

It is possible to analyze the tendencies of the world’s development with references to the statistical approach and use this approach as the means to organize the everyday life according to these trends. Furthermore, many people focus on the results of the statistical researches not only at the elementary level in their daily life but also as the part of their work. Thus, accounting, economics, logistics, and many other spheres of the knowledge use statistics (Black, 2009). Moreover, working with their computers, people often refer to the statistical analysis of the data in order to receive the average result or form the picture of the process’s development (Mann, 2010).

Today, it is not necessary for people to examine and test a lot of material to get the information about its appropriateness for the people’s everyday activity or about tendencies of the phenomenon’s progress because all these data can be taken in the form of the statistical graphs or percentages. There are many daily questions the answers to which are hidden in the statistical data.

Black, K. (2009). Business statistics: Contemporary decision making . USA: Wiley.

Bluman, A. G. (2009). Elementary statistics: A step by step approach. New York, NY: McGraw-Hill.

Mann, P. S. (2010). Introductory statistics . Hoboken, NJ: Wiley.

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The Importance of Statistics in Daily Life

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Utilizing statistics for decision-making, understanding trends and patterns, evaluating claims and evidence, limitations and challenges in statistics.

• Agresti, A. (2015). Foundations of linear and generalized linear models. John Wiley & Sons.
• Coleman, J. S. (1990). Foundations of Social Theory. Cambridge, MA: Belknap Press of Harvard University.
• Kabacoff, R. (2015). The R graphics cookbook. O'Reilly Media, Inc.
• Mendenhall, W., Beaver, R. J., & Beaver, B. M. (2016). Introduction to probability and statistics. Cengage Learning.

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Reflection on Statistical Analysis

In Statistics for the Social Sciences, I have learned various techniques working with sociological data. Before this class began I was nervous that I would not understand the given material. After a couple of classes, I realized how important the information was in analyzing data. Not only is the information important, but it is also interesting to learn. I learned how to calculate data and methods by hand, in SPSS, and by R. Although calculating methods by hand is long, each step is important to find the result. Calculating data by hand and in computer software has taught me how to analyze statistics. All of the statistical methods and models have challenged my mind.

Throughout the course, I was also able to learn concepts of social statistics, testing hypotheses, and computing statistics. I was uncertain of all the statistical work that goes into research. Learning all of the material allowed me to view statistical research in a different light. The methods that I felt were the most challenging included; Z Scores, T-tests, and Chi-Square. As I found these difficult, I felt accomplished when completing the handwork. All three methods allowed me to learn the importance of comparing data to one another, understand probability, and test the significance of data. Overall, the course has helped me learn ways to use data in the various scenarios, computing data in SPSS/R, and using data for future uses.

Statistical research is important within a class, however, there is also the importance in a larger context. Statistics in social science matters in a larger context because data can be used in various ways. Research and statistics can be used in making decisions in government, education, and medical advances. Most importantly, what I have learned it can answer important questions. The methods used throughout the course can help view data in larger population scenarios.

The skills learned can also be used in a larger context in a career and a technology aspect. I do believe calculating methods by hand is very important, however, larger data sets can be analyzed by computer software. SPSS is an older system and R is a newer system. Both are used to analyze large data sets. With that being said, data is easier to analyze through computer software. The data can help people in careers who may have to analyze data as a career. It could also allow questions to be answered with large data sets to further research.

With what I have learned in this course, I will use these skills in graduate school. I will be able to research, collect, and analyze data. I could also use the skills I learned in my future career. I am pursuing a career in Clinical Mental Health Counseling after graduate school. Having a career like this would allow me to record health, depression, and or anxiety data collections. Overall, this course has and will allow me to continue to learn more about the methods, research, and statistical social science.

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Statistics in Early Childhood and Primary Education pp 201–215 Cite as

Teachers’ Reflection on Challenges for Teaching Probability in the Early Years

• Efi Paparistodemou 5 &
• Maria Meletiou-Mavrotheris 6  
• First Online: 24 July 2018

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Part of the book series: Early Mathematics Learning and Development ((EMLD))

The present research focuses on the early childhood teachers’ reflection on designing and implementing probability tasks. Five early childhood teachers participated in this research, which was organized in three stages: design of lesson plan, classroom implementation and reflection. The researchers analysed the design of each lesson, observed teachers implementing their lesson and interviewed them while they reflected on their instruction. Teachers discussed critical incidents that occurred through their teaching, and they reflected on challenges for teaching probability. An initial analysis of the collected data indicates that early childhood teachers appreciated the importance of using tools and real-life scenarios in their classrooms for teaching stochastics. The study also provided some useful insights into the varying levels of attention that teachers paid to different kinds of activities during their lesson implementation, and into the different types of instructional material they used. Moreover, the findings also show that early childhood teachers’ attention to different aspects of probability tasks can be developed through a reflective process on their teaching.

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Paparistodemou, E., Meletiou-Mavrotheris, M. (2018). Teachers’ Reflection on Challenges for Teaching Probability in the Early Years. In: Leavy, A., Meletiou-Mavrotheris, M., Paparistodemou, E. (eds) Statistics in Early Childhood and Primary Education. Early Mathematics Learning and Development. Springer, Singapore. https://doi.org/10.1007/978-981-13-1044-7_12

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Research in probability and statistics: Reflections and directions

Probability and statistics (stochastics) are viewed as necessary for all students no matter their ambitions. However, there are barriers to the effective teaching of both stochastics and problem solving: 1) getting stochastics into the mainstream of the mathematical science school curriculum; 2) enhancing teachers' background and conceptions of probability and statistics; 3) confronting students' and teachers' beliefs about probability and statistics. Psychologists and mathematics educators should work collaboratively to diminish misconceptions. Doing so combines the roles of observer, describer, and intervener. Research in stochastics suggests that heuristics that are used intuitively by learners impede the conceptual understanding of concepts such as sampling. This paper reviews the research on judgemental heuristics and biases, conditional probability and independence (i.e., causal schemes), decision schema (i.e., outcome approach), and the mean. Learners have difficulties in these areas, however, evidence is contradictory as to whether training in stochastics improves performance and decreases misconceptions. The conclusion emerging from this research is that probability concepts can and should be introduced into the school at an early age. Instruction that is designed to confront misconceptions should encourage students to test whether their beliefs coincide with those of others, whether they are consistent with their own beliefs about other related things, and whether their beliefs are born out with empirical evidence. Computers can be used to provide both an exploratory and representational aspect of the discipline. The role of teachers in this type of environment and the issue of whether stu- dents should use artificial or real data sets should be considered.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education

Sunday, March 26, 2017

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