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

      False

 

Question 2. 2. The Chi-square test for independence needs a known (rather than calculated) expected distribution. (Points : 1)
      True 

      False

 

Question 3. 3. The Chi-square test measures differences in frequency counts rather than differences in size (such as the t-test and ANOVA). (Points : 1)
      True 

      False

 

Question 4. 4. A confidence interval is generally created when statistical tests fail to reject the null hypothesis – that is, when results are not statistically significant. (Points : 1)
      True 

      False

 

Question 5. 5. The distribution for the goodness of fit test equals k-1, where k equals the number of categories. (Points : 1)
      True 

      False

 

Question 6. 6. The Chi-square test results having expected values of less than 5 in a cell may produce a greater likelihood of having type I errors (wrongly rejecting the null hypothesis). (Points : 1)
      True 

      False

 

Question 7. 7. The Chi-square test is very sensitive to small differences in frequency differences. (Points : 1)
      True 

      False

 

Question 8. 8. 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)
      True 

      False

 

Question 9. 9. The percent confidence interval is the range having the percent probability of containing the actual population parameter. (Points : 1)
      True 

      False

 

Question 10. 10. Compared to the ANOVA test, Chi-Square procedures are not powerful (able to detect small differences). (Points : 1)
      True 

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

      True

    • Not rated

      10 MCQ

      1. The Chi-square test is very sensitive to small differences in frequency differences.

      1. The Chi-square test is very sensitive to small differences in frequency differences. (Points : 1)

      True

      False

    • Question 1.1.For a one sample confidence interval, the interval is calculated around the estimated population mean or standard (μm). (Points : 1)

    • 1. The Chi-square test is very sensitive to small differences in frequency differences. (Points : 1)

      True

      False



      Question 2. 2. The probability that the actual population mean will be outside …

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

      True
      False

      Question 2. 2. Chi-square tests rarely have type I errors. …

    • Question 1.1. The distribution for the goodness of fit test equals k-1, where k equals the number of categories. (Points : 1)

      True

      False

      Question 2.2. While rejecting the null …