May 1, 2024
3 minute read
The chi-square test is a statistical test used to determine whether there is a significant difference between the expected frequencies and the observed frequencies of events. It is a non-parametric test, meaning that it does not make any assumptions about the distribution of the data. The chi-square test is widely used in various fields, including medicine, biology, psychology, and social sciences.
What is the Chi-Square Test?
The chi-square test is based on the chi-square statistic, which is a measure of the discrepancy between the expected and observed frequencies. The chi-square statistic is calculated as the sum of the squared differences between the expected and observed frequencies, divided by the expected frequencies.
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Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Chi-Square Test.
Provides a detailed overview of the chi-square test of goodness of fit, covering its theoretical foundations, applications, and interpretation. It is an essential resource for researchers and practitioners in various fields who need to analyze categorical data.
This short but informative book provides a concise introduction to chi-square tests. It covers the basics of the test and its applications in various fields.
Comprehensive guide to performing chi-square tests in R, a popular statistical software. It covers various aspects of chi-square testing, including data preparation, model fitting, and interpretation. It is suitable for both beginners and experienced R users.
This textbook provides a thorough introduction to statistical methods commonly used in psychology research, including the chi-square test. It is written in a clear and accessible style, making it ideal for undergraduate and graduate students.
Covers a wide range of nonparametric statistical methods, including the chi-square test. It provides detailed explanations and examples, making it a useful reference for researchers and practitioners.
This classic text on statistical power analysis discusses the role of the chi-square test in determining the sample size required for a study to achieve statistical significance.
This comprehensive textbook covers advanced statistical methods, including the chi-square test. It is suitable for graduate students and researchers in various fields who need to analyze complex data.
This French-language textbook covers inferential statistics, including the chi-square test. It is written in a clear and concise style and includes numerous examples and exercises.
This Italian-language textbook provides a comprehensive overview of statistics, including the chi-square test. It is suitable for students and researchers in various fields.
This Spanish-language textbook covers basic statistics for social sciences, including the chi-square test. It is written in a clear and accessible style, making it suitable for undergraduate students.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/pwxx82/chi
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