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Statistics for Managers

Daniel Kevins

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Question 1.1. The one-sample t-test differs from the z-test in which way?
@Answer found in section 4.3 The One-sample t-Test, in Statistics for Managers (Points : 1)

  There are no parameter values involved in a t-test.
  The t-test is more sensitive to minor differences between sample and population.
  With the t-test one can be confident of the normality of the data.
  The t-test requires no <known> parameter standard error of the mean.

Question 2.2. What is the relationship between the power of a statistical test and decision errors?
@Answer found in section 4.3 The One-sample t-Test, in Statistics for Managers (Points : 1)

  Powerful tests minimize the risk of decision errors.
  Powerful tests are more inclined to type II than type I errors.
  Powerful tests compensate for decision errors with stronger effect sizes.
  Powerful tests minimize type II errors.

Question 3.3. Which of the following is a provision of the central limit theorem? (Points : 1)

  A skewed distribution will remain skewed however it is plotted.
  There are limits to the range of scores that can be fitted to a distribution.
  A distribution based on sample means will be normal.
  There will always be theoretical differences between distributions.

Question 4.4. The mean of the distribution of sample means will have the same value as the mean of the distribution of individual scores upon which it is based. (Points : 1)

True
False

Question 5.5. The z- test requires an estimate of the population standard deviation. (Points : 1)

True
False

Question 6.6. Why do the critical values change with degrees of freedom for the t-tests?
@Answer found in section 4.3 The One-sample t-Test, in Statistics for Managers
(Points : 1)

  Different degrees of freedom define different t distributions.
  Because the critical values are calculated directly from degrees of freedom.
  The degrees of freedom reflect the value of SE_M.
  The degrees of freedom are indexed to the M – μ_M difference.

Question 7.7. The standard error of the mean can be calculated by dividing μ by the square root of the number of values in the distribution. (Points : 1)

True
False

Question 8.8. The standard error of the mean is actually the standard deviation of all of the means that make up the distribution of sample means. (Points : 1)

True
False

Question 9.9. The desired sample size depends only the size of the population to be tested. (Points : 1)

True
False

Question 10.10. What statistic measures data variability in both groups in an independent t-test?
@Answer found in section 4.5 The Independent Samples t-Test, in Statistics for Managers (Points : 1)

  The critical value of t.
  The M₁
– M₂ difference.
  The calculated value of t.
  The SE_d

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Daniel Kevins

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