Chi Squared Flashcards
What is the Chi-Square test used for?
It is used to test the relationship between two categorical variables.
What types of data does the Chi-Square test analyze?
Categorical data (nominal or ordinal).
What are the assumptions of the Chi-Square test?
Data must be categorical.
Observations must be independent.
Expected frequency in each cell should be ≥ 5.
What are the two main types of Chi-Square tests?
Chi-Square Test for Independence (relationship between variables).
Chi-Square Goodness-of-Fit Test (how well data fit expected distribution).
What is the null hypothesis in a Chi-Square test?
That there is no association between the categorical variables.
What is the formula for the Chi-Square test statistic?
χ 2 =∑ ((O−E) 2/E)
Where:
O = Observed Frequency
E=Expected Frequency
How do you calculate expected frequencies in a Chi-Square test?
E=RowTotal×ColumnTotal/GrandTotal
What does a significant Chi-Square test result indicate?
That there is a statistically significant relationship between the variables.
What is the degrees of freedom (df) formula for a Chi-Square test?
df=(rows−1)×(columns−1)
What is the p-value in the Chi-Square test used for?
To determine whether to reject the null hypothesis based on the significance level.
When should you use Fisher’s Exact Test instead of Chi-Square?
When sample sizes are small and expected frequencies are below 5.
What are common applications of the Chi-Square test?
Examining survey responses across groups.
Testing if preferences differ by demographic.
Analyzing contingency tables in marketing research.
How can Chi-Square test results be affected by sample size?
Larger samples can detect smaller differences, while small samples may lack power.
What are the limitations of the Chi-Square test?
Sensitive to sample size.
Cannot establish causation.
Requires categorical data only.
What does it mean if the Chi-Square statistic is large?
It indicates a larger difference between observed and expected frequencies, suggesting a stronger relationship.
