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Two Means - Unknown Variances Hypothesis Test - Excel quiz

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  • What Excel function is used to perform a hypothesis test for two population means?
    The =T.TEST function is used in Excel to perform a hypothesis test for two population means.
  • What does the =T.TEST function in Excel directly calculate from your data?
    It directly calculates the p-value from your data arrays.
  • What is the null hypothesis when comparing two population means?
    The null hypothesis is that the two means are equal.
  • How do you specify a one-tailed test in the =T.TEST function?
    You enter '1' for the tails input to specify a one-tailed test.
  • What value do you enter for the 'type' input in =T.TEST for a regular two-sample t-test?
    You enter '3' for the type input to indicate a regular two-sample t-test.
  • What is the alternative hypothesis if you are testing whether the new UI loads faster than the old UI?
    The alternative hypothesis is that the mean loading time for the new UI is less than that for the old UI (μ1 < μ2).
  • What do you compare the p-value to in order to make a decision about the null hypothesis?
    You compare the p-value to the significance level α.
  • What conclusion do you draw if the p-value is greater than α?
    If the p-value is greater than α, you fail to reject the null hypothesis.
  • What does failing to reject the null hypothesis imply about the alternative hypothesis?
    It implies there is not enough evidence to conclude the alternative hypothesis is true.
  • What are the first two inputs for the =T.TEST function in Excel?
    The first input is array1 (first data set), and the second input is array2 (second data set).
  • How does the =T.TEST function handle left-tailed and right-tailed tests?
    It gives the probability of the smaller of the two tails when you enter '1' for tails.
  • What is the significance level (α) used in the example provided?
    The significance level used is 0.05.
  • What was the p-value calculated in the example, and what was the decision?
    The p-value was about 0.22, which is greater than 0.05, so the null hypothesis was not rejected.
  • What is the practical conclusion if the p-value is greater than α in the UI loading time example?
    There is not enough evidence to conclude that the new UI loads faster than the old UI.
  • What should you do if you want more practice with two means t-tests in Excel?
    You should check out additional examples for more practice.