Chi-Square Test of Independence - Group 5

1. What is the Chi Square Test of Independence used for?

• a. Testing a hypothesis about the distribution of a continuous variable

• b. Testing a hypothesis about the distribution of a categorical variable

• c. Testing the correlation between two continuous variables

• d. Testing the correlation between two categorical variables

2. How many types of Pearson's chi-square tests are there?

• a. One

• b. Two

• c. Three

• d. Four

3. What does the Chi Square Test of Independence allow you to test?

• a. Whether a variable has a normal distribution

• b. Whether two variables are related to each other

• c. Whether a sample mean is significantly different from a population mean

• d. Whether two samples are significantly different from each other

4. What does the observed frequency distribution describe?

• a. How observations are distributed between different groups

• b. The expected frequency distribution of a categorical variable

• c. The probability of belonging to a certain group of one variable

• d. The correlation between two categorical variables

5. What is the formula for the Chi Square Test of Independence?

• a. X^2 = (x - μ) / (σ / sqrt(n))

• b. X^2 = (x̄ - μ) / (s / √n)

• c. X^2 = sqrt [ Σ ( xi - μ )^2 / N ]

• d. Χ^2 = Σ[(O - E)² / E]

6. When should someone use a Chi Square Test of Independence?

I. A hypothesis about possibly multiple categorical variables is needed.

II. Five minimum observations expected in each group/combination of groups are present.

III. The sample was not systematically selected from the population but rather randomly selected.

IV. The sample was not randomly selected from the population but rather systematically selected.

• A. I, II, III

• B. I, II, IV

• C. I and III only

• D. I and IV only

7. What should be your final step in conducting the Chi Square Test of Independence?

• A. Reject/Accept null hypothesis

• B. Find the critical chi-square value in a chi-square critical value table or using statistical software

• C. Calculate Chi-square critical value

• D. Create a table of frequencies

8. If you accept the null hypothesis, you can conclude that your data are significantly different from what you expected.

• True

• False

9. One should use the Chi Square formula to come up with the Chi Square value.

• True

• False

10. If the Chi square value is greater than the critical value, one must accept the null hypothesis.

• True

• False