Chi Square Review

What is a p-value in the context of Chi-Square tests?

• The p-value indicates the probability of observing the data if the null hypothesis is true.

• The p-value measures the strength of the relationship between two variables.

• The p-value is the threshold for determining the sample size needed for a test.

• The p-value represents the likelihood of the alternative hypothesis being true.

What is the purpose of the Chi-Square test in research?

• To analyze categorical data and determine if observed frequencies differ from expected frequencies.

• To measure the strength of a linear relationship between two variables.

• To compare means between two or more groups.

• To assess the reliability of a measurement instrument.

What are degrees of freedom in a Chi-Square test?

• The number of categories in the test

• The number of values that can vary in the calculation

• The total number of observations in the sample

• The number of categories minus one

What is the Chi-Square Test for Homogeneity?

• It compares the distribution of a categorical variable across different populations.

• It tests the mean of a single population against a known value.

• It assesses the relationship between two continuous variables.

• It determines the variance within a single population.

What is the null hypothesis in a Chi-Square test?

• The null hypothesis states that there is no association between the categorical variables.

• The null hypothesis states that all categorical variables are independent.

• The null hypothesis states that there is a strong correlation between the variables.

• The null hypothesis states that the sample means are equal.

What is the minimum expected frequency for a Chi-Square test?

• The expected frequency for each category should be greater than or equal to 5.

• The expected frequency for each category should be greater than or equal to 10.

• The expected frequency for each category should be greater than or equal to 15.

• The expected frequency for each category should be greater than or equal to 20.

What is the Chi-Square Test for Independence?

• It assesses whether two categorical variables are independent of each other.

• It measures the correlation between two continuous variables.

• It tests the mean difference between two groups.

• It evaluates the variance within a single categorical variable.

What is the significance level (alpha) commonly used in Chi-Square tests?

• 0.01

• 0.05

• 0.10

• 0.15

What is the alternative hypothesis in a Chi-Square test?

• The alternative hypothesis states that there is an association between the categorical variables.

• The alternative hypothesis states that there is no association between the categorical variables.

• The alternative hypothesis states that the sample means are equal.

• The alternative hypothesis states that the data is normally distributed.

How do you calculate degrees of freedom for a Chi-Square test?

• Degrees of freedom = (number of rows - 1) * (number of columns - 1) for a contingency table.

• Degrees of freedom = number of rows + number of columns - 2 for a contingency table.

• Degrees of freedom = (number of rows + number of columns) for a contingency table.

• Degrees of freedom = (number of rows - 1) + (number of columns - 1) for a contingency table.