



How can misinterpretation of chi-square results lead to incorrect conclusions?
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what is chi square test formula
- Can the chi-square statistic be negative?
- Do standard non-parametric tests for ordinal data handle ties differently than how a chi-square test would implicitly treat them?
- What are the limitations of using the chi-square statistic as the sole criterion for model selection?
- What is the purpose of squaring the difference between observed and expected frequencies in the formula?
- How is the chi-square test used in genetics (e.g., testing for Hardy-Weinberg equilibrium)?
- What are the implications of having a very large sample size on the statistical significance of a chi-square test (i.e., even small differences might become significant)?
- Can the chi-square test be used for repeated measures of categorical data?
- How does the chi-square test relate to the analysis of textual data with categorical codes?
- What are other statistical methods used in image analysis with categorical data?
- What are methods for handling incomplete categorical data (e.g., imputation)?
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