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How do you learn and update your skills in nonparametric statistics?

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Nonparametric statistics are useful for analyzing data that do not follow the assumptions of parametric methods, such as normality, homogeneity, or linearity. They can also handle complex or irregular data structures, such as ordinal, categorical, or ranked data. However, learning and updating your skills in nonparametric statistics can be challenging, as there are many different techniques and applications to choose from. Here are some tips to help you master this field of statistics.

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1 Know the basics

Before diving into the advanced topics of nonparametric statistics, you should have a solid foundation of the basic concepts and principles. You should understand what nonparametric tests are, how they differ from parametric tests, and when to use them. You should also be familiar with the common nonparametric tests, such as the Wilcoxon, Mann-Whitney, Kruskal-Wallis, Friedman, or Chi-square tests, and how to interpret their results. You can find many online resources, books, or courses that cover these topics, such as the Nonparametric Statistics for Non-Statisticians by Gregory W. Corder and Dale I. Foreman.

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2 Learn by doing

One of the best ways to learn and update your skills in nonparametric statistics is to practice with real or simulated data. You can use software tools such as R, Python, SPSS, or SAS to perform nonparametric analyses and visualize the results. You can also find datasets and examples from various domains — such as social sciences, biology, engineering, or economics — that illustrate the use of nonparametric methods. You can try to replicate the analyses, modify the parameters, or compare different methods to see how they affect the outcomes.

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?? Mark Freeman II

Data Engineering | Tech Lead @ Gable.ai | O’Reilly Author: Data Contracts | LinkedIn [in]structor | Founder @ On the Mark Data
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Learning statistics is just like climbing up a spiral staircase. You often revisit the same topics over and over again, but each time you are a little bit higher in understanding. To best understand nonparametric statistics you first need to really understand the parametric statistics (e.g. your population has a normal distribution). Specifically, focus on 1) the assumptions of the test, and 2) the limitations of the test. Once you realize that the appropriate tests assumptions are not met, typically "normality", you then explore the nonparametric version of the test. A great example of this is the "paired t-test" and the "wilcoxon rank sum test."

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Fred Viole

OVVO Financial Systems | ovvolabs.com
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Over the last decade+, I have been expanding the capabilities and applications of nonparametric statistics by employing partial moments. By utilizing the "NNS" R-package, I have found that deviating from traditional, ineffective techniques can provide distinctive and valuable perspectives, as shown in the examples below. https://github.com/OVVO-Financial/NNS/blob/NNS-Beta-Version/examples/index.md

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Matt Stewart

Senior Scientist at QuidelOrtho
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I recommend "Learning Minitab" from Richard Chua on LinkedIn Learning. This is a great course and with workbooks you can follow through the steps and replicate the analysis first-hand. https://www.dhirubhai.net/learning/learning-minitab-13972912/comparing-medians-using-nonparametric-tests?u=2202801

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3 Explore new developments

New methods and applications are being developed and published regularly. Keep up with the latest research and trends in this area by reading journals, blogs, or newsletters that focus on nonparametric statistics. You can also attend webinars, workshops, or conferences that showcase the current state-of-the-art and future directions of nonparametric statistics. Some examples of these sources are the Journal of Nonparametric Statistics, Frank Harrell's Statistical Thinking blog, and the International Conference on Robust Statistics.

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4 Connect with others

Another way to learn and update your skills in nonparametric statistics is to connect with other people who share your interest and expertise in this field. You can join online communities, forums, or groups that discuss nonparametric statistics, such as the Nonparametric Statistics Stack Exchange. Network with experts, mentors, or peers, and seek feedback from others.

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5 Review and refresh

You should review and refresh your skills regularly to avoid forgetting or missing important concepts or techniques. Use online quizzes, flashcards, or games to test your knowledge and recall of nonparametric statistics. Also revisit your previous projects or analyses and see if you can improve them with new or different methods. Take refresher courses or workshops that cover the essential topics of nonparametric statistics, and read books or articles that summarize or synthesize the key ideas or applications. One terrific option to consider is the Handbook of Parametric and Nonparametric Statistical Procedures by David J. Sheskin.

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Fraser Clark

Econometrics Adviser at the Competition and Markets Authority
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A great textbook (but more advanced) for those interested in the theoretical background is Nonparametric Econometrics: Theory and Practice by Jeffrey Racine and Qi Li

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Aaron Gavin

Professor of Business in Economics and Quantitative Analysis. Startups and Going Bigger
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Society and Statistics is offered on You Tube. It is provided by Aaron Gavin's channel who offers it for review and educational purposes. Some good guitar too.

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How do you learn and update your skills in nonparametric statistics?

1

2

3

4

5

6

1 Know the basics

2 Learn by doing

3 Explore new developments

4 Connect with others

5 Review and refresh

6 Here’s what else to consider

Statistics

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How do you learn and update your skills in nonparametric statistics?

1

2

3

4

5

6

1 Know the basics

2 Learn by doing

3 Explore new developments

4 Connect with others

5 Review and refresh

6 Here’s what else to consider

Statistics

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