100 Statistical Tests
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As the number of statistical tests has increased, so has the need for a single source of reference. Bringing together the hundred most commonly used tests, this volume provides just such an indispensable aid for student and statistician alike. The introduction discusses the principles of hypothesis-testing. Examples of the procedure for selected tests follow, illustrating statistical method in practice. The purpose of each test is summarized, and a classification chart identifies their interconnections and contexts of use. The bulk of the book consists of clear, concise outlines of the objective, method, strengths and limitations of each test, giving sample data. All the relevant tables of critical values are included.
Basic and Advanced Statistical Tests
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This book focuses on extraction of pertinent information from statistical test outputs, in order to write result sections and/or accompanying tables and/or figures. The book is divided into two encompassing sections: Part I - Basic Statistical Tests and Part II - Advanced Statistical Tests. Part I includes 9 basic statistical tests, and Part II includes 7 advanced statistical tests. Each chapter provides the name of a basic or advanced statistical test, a brief description, examples of when to use each, a sample scenario, and a sample results section write-up. Depending on the test and need, most chapters provide a table and/or figure to accompany the write-up. The purpose of the book is to provide researchers with a reference manual for writing results sections and tables/figures in scholarly works. The authors fill a gap in research support manuals by focusing on sample write-ups and tables/figures for given statistical tests. The book assists researchers by eliminating the need to comb through numerous publications to determine necessary information to report, as well as correct APA format to use, at the close of analyses.
STATISTICAL TESTS
Statistical analysis is a procedure that allows you to make quantitative assessments about a process or set of processes. The goal is to see if there is enough information to "reject" a theory or hypothesis about how the process works.
Choosing the Correct Statistical Test in SAS, Stata, SPSS and R. (n.d.). Introduction to SAS. UCLA: Statistical Consulting Group. Retrieved May 30, 2022, from https://stats.oarc.ucla.edu/other/mult-pkg/whatstat/
Use it WHEN
The mean represents the center of data distribution
The Sample size is large
The data is normally distributed
Data that is assumed to have a normal distribution can be analyzed using the following statistical analyses:
t-tests
ANOVA
Regression Analysis
Correlation Coefficient
Bevans, R. (2022, May 6). Statistical tests: which one should you use? Scribbr. https://www.scribbr.com/statistics/statistical-tests/
Nonparametric tests, often known as distribution-free tests, are statistical tests that make no assumptions about the data's distribution. Nonparametric tests are based on ordinal variables or the rank of values in the data.
Use it WHEN
The median represents the center of data distribution
The Sample size is large or small
The data is not normally distributed
Data that is assumed to not have a normal distribution can be analyzed using the following statistical analyses:
1-sample sign test
1-sample Wilcoxon Signed Rank test
Friedman test
Kruskal-Wallis test
Mann-Whitney test
Mood’s Median test
Spearman Rank Correlation
S, S. (2017, September 1). Difference Between Parametric and Nonparametric Test (with Comparison Chart). Key Differences. https://keydifferences.com/difference-between-parametric-and-nonparametric-test.html
Each parametric test has its equivalent non-parametric test that is given in the below image
Inferential statistics. (n.d.). Slidetodoc.Com. https://slidetodoc.com/inferential-statistics-introduction-descriptive-statistics-judgmentsinferences-related-to/
