### Critical Hypothesis – Statistic Quiz

The key terms in these Statistics chapters include Chi-Square Test, Population, Distribution, Goodness of Fit & The Null Hypothesis, Critical Hypothesis.

What conclusion is appropriate if a chi-square test produces a chi-square statistic near zero?

**There a good fit between the sample data and the null hypothesis**

What happens to the critical value for a chi-square test if the size of the sample is increased?

**The critical value depends on the number of categories, not the sample size**

A large value for the chi-square statistic indicates

**the sample data (observed values) do not fit the null hypothesis**

The term expected frequencies refers to

**the frequencies computed from the null hypothesis**

The chi-square distribution tends to be symmetrical with a mean of μ = 0.

**False**

How do you compute df for the chi-square test for goodness of fit?

**Goodness of fit**

What values are specified by the null hypothesis for the chi-square test for goodness of fit?

**Proportions for the entire population**

What happens to the critical value for a chi-square test if the size of the sample is increased?

**The critical value depends on the number of categories, not the sample size**

What happens to the shape of the chi-square distribution as the df value increases?

**The mode (highest point) of the distribution moves to the right**

What conclusion is appropriate if a chi-square test produces a chi-square statistic near zero?

**There a good fit between the sample data and the null hypothesis**

The chi-square test for goodness of fit evaluates

**the shape or proportions for a population distribution**

The chi-square test for independence is similar to an independent-measures t test because it can be used to evaluate the difference between two populations or two treatment conditions.

**True**

For the expected frequencies in a chi-square test for independence, the proportions for any row are exactly the same as the proportions in every other row.

**True**

A chi-square test should not be used if any observed frequency is less than five.

**True**

The observed frequencies for a chi-square test can be fractions or decimal values.

**False**

For a fixed level of significance, the critical value for chi-square decreases as the size of the sample increases.

**False**

A chi-square test for independence produces a chi-square statistic with df = 2. The data for this research study form a 2X2 matrix with four separate categories.

**False**

For a fixed level of significance, the critical value for chi-square decreases as the size of the sample increases.

**False**

What conclusion is appropriate if a chi-square test produces a chi-square statistic near zero?

**There a good fit between the sample data and the null hypothesis**

What happens to the critical value for a chi-square test if the size of the sample is increased?

**The critical value depends on the number of categories, not the sample size**

A large value for the chi-square statistic indicates

**the sample data (observed values) do not fit the null hypothesis**

The term expected frequencies refers to

**the frequencies computed from the null hypothesis**

The chi-square distribution tends to be symmetrical with a mean of μ = 0.

**False**

How do you compute df for the chi-square test for goodness of fit?