Question 1. The goodness of fit test determines if a data set distribution/shape matches a standard or hypothesized distribution. (Points : 1) True False Question 2. 2. The goodness of fit test can be used for a single or multiple set

Question 1. The goodness of fit test determines if a data set distribution/shape matches a standard or hypothesized distribution. (Points : 1)

Question 2. 2. The goodness of fit test can be used for a single or multiple set (rows) of data, such as comparing male and female age distributions with an expected distribution at the same time. (Points : 1)

Question 3. 3. In confidence intervals, the width of the interval depends only on the variation within the data set. (Points : 1)

Question 4. 4. Statistical significance in the Chi-square test means the population distribution (expected) is not the source of the sample (observed) data. (Points : 1)

Question 5. 5. The null hypothesis for the test of independence states that no correlation exists between the variables. (Points : 1)

Question 6. 6. The goodness of fit test null hypothesis states that the sample data does not match an expected distribution. (Points : 1)

Question 7. 7. The probability that the actual population mean will be outside of a 98% confidence interval is (Points : 1)

Question 8. 8. Point estimates provide less confidence in indicating a parameter’s value than a confidence interval. (Points : 1)

Question 9. 9. The distribution for the goodness of fit test equals k-1, where k equals the number of categories. (Points : 1)

Question 10. 10. For a one sample confidence interval, if the interval contains the μ_m , the  corresponding t-test will have a statistically significant result – rejecting the null hypothesis. (Points : 1)