# Multiple choice questions from Chi-Square test

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1. In a chi-square test, the sample data are called observed frequencies.

True

False

2. One advantage of the chi-square tests is that they can be used when the data are measured on a nominal scale.

True

False

3. A chi-square test for goodness of fit is used to evaluate a hypothesis about how a population is distributed across three categories. If the researcher uses a sample of n = 100 participants, then the chi-square test will have df = 99.

True

False

4. The chi-square test for independence requires that each individual be categorized on two separate variables.

True

False

5. For the chi-square test for goodness of fit, what is the value of df for a test with four categories and a sample of n = 100?

96

4

3

99

6. The chi-square distribution is

positively skewed, with no values less than zero.

negatively skewed, with no values greater than zero.

symmetrical, centered at a value determined by the degrees of freedom.

symmetrical, centered at a value of zero.

7. A researcher obtains a value of -8.50 for a chi-square statistic. What can you conclude because the value is negative?

the observed frequencies are consistently larger than the expected frequencies

The researcher made a mistake. The value of chi-square cannot be negative.

the expected frequencies are consistently larger than the observed frequencies

there are large differences between the observed and expected frequencies

8. A chi-square test for independence is used to evaluate the relationship between two variables. If one variable is classified into 4 categories and the other variable is classified into 2 categories, then the chi-square statistic will have

df = 6

cannot determine the value of df from the information provided

df = 3

df = 8

9. The sample data for a chi-square test are called ________.

observed proportions

observed frequencies

expected proportions

expected frequencies

10. In the chi-square test for independence, the null hypothesis states that

there is no relationship between the two variables being examined.

there is a relationship between the two variables being examined.

there is no difference between the two variables being examined.

there is a difference between the two variab

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