An Introduction to Statistics for Librarians (Part Three): An Introduction to Statistical Tests

المؤلفون

DOI:

https://doi.org/10.18060/27969

الكلمات المفتاحية:

parametric tests، non-parametric tests، p-values، statistical significance

الملخص

In the previous two columns, types of data, central tendency and distribution were discussed. This installment will build upon that content and explore various statistical tests. Three scenarios are introduced to illustrate how tests can be selected based on the type of data, the number of groups, and the distribution of the data. The column discusses interpreting test results, including challenges around establishing causation and the potential overreliance on p-values.

المراجع

Bakker CJ. An Introduction to Statistics for Librarians (Part One): Types of Data. Hypothesis Res J Health Inf Prof. 2022;34(1). doi:10.18060/26428

Bakker CJ. An Introduction to Statistics for Librarians (Part Two): Frequency Distributions and Measures of Central Tendency. Hypothesis Res J Health Inf Prof. 2023;35(1). doi:10.18060/27162

Carlson S. Data analysis: Making sense of the numbers. Presented at: Department of Family Medicine & Community Health, University of Minnesota; 2016; Minneapolis, MN.

Hoskin T. Parametric and Nonparametric: Demystifying the Terms. Mayo Clinic. https://www.mayo.edu/research/documents/parametric-and-nonparametric-demystifying-the-terms/doc-20408960

Herzog MH, Francis G, Clarke A. Variations on the t-Test. In: Understanding Statistics and Experimental Design: How to Not Lie with Statistics. Springer International Publishing; 2019:51-59. Accessed May 28, 2022. http://library.oapen.org/handle/20.500.12657/23029

Sarty GE. Introduction to Applied Statistics for Psychology Students. University of Saskatchewan Open Press; 2022. Accessed December 30, 2023. https://openpress.usask.ca/introtoappliedstatsforpsych/

Jarman KH. Bunco, bricks, and marked cards: Chi-squared tests and how to beat a cheater. In: Beyond Basic Statistics: Tips, Tricks, and Techniques That Every Data Scientist Should Know. Wiley; 2015:47-68.

Amrhein V, Greenland S, McShane B. Scientists rise up against statistical significance. Nature. 2019;567(7748):305-307. doi:10.1038/d41586-019-00857-9

Kennedy-Shaffer L. Before p < 0.05 to Beyond p < 0.05: Using History to Contextualize p-Values and Significance Testing. Am Stat. 2019;73(sup1):82-90. doi:10.1080/00031305.2018.1537891

التنزيلات

منشور

2024-03-27

كيفية الاقتباس

Bakker, C. (2024). An Introduction to Statistics for Librarians (Part Three): An Introduction to Statistical Tests. Hypothesis: Research Journal for Health Information Professionals, 36(1). https://doi.org/10.18060/27969

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