Comparing two Means

by David Spade, PhD

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The lecture Comparing two Means by David Spade, PhD is from the course Statistics Part 2. It contains the following chapters:

Before carrying out any inference for the difference between two means, what is the first thing that should be done?

The data in each group should be plotted using side-by-side box plots in order to look at the differences in the two distributions.
The data should be plotted in one boxplot in order to look at the differences in the two distributions.
Nothing needs to be done before using the two-sample t-procedures.
The data should be grouped together and examined in one histogram in order to look at the differences between the two groups.

Which of the following is not a condition for the use of the two-sample t-interval?

When is the pooled t-test appropriate?

The pooled t-test is appropriate when the spreads in each group are roughly the same and all other conditions for the two-sample t-procedures are satisfied.
The pooled t-test is appropriate when both groups are independent.
The pooled t-test is appropriate in any situation in which we are comparing two population means.
The pooled t-test is appropriate when none distribution appears normal.

Which of the following is true regarding the differences between the two-sample t-procedures and the pooled t-procedures?

Once the test statistic is calculated along with the degrees of freedom for the test statistic, the computation of the critical value is done in the same way for each procedure.
The standard error calculations are the same for each procedure.
The degrees of freedom are the same for the two procedures.
The test statistic is calculated in the same way for each procedure, including the standard error calculation.

Which of the following is true of two-sample inference?

A significant difference in means or proportions is not necessarily evidence of cause.
Looking at plots to check conditions before performing inference will cause problems with the inference procedure.
Applying the two-sample t-procedures is fine to do even if the data are not suitably randomized.
It is not appropriate to apply the t-procedures if the groups are not independent.

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