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Which of the following situations would result in a t-test that not likely to be accurate? Choose all that apply

a. data sets that had normal distributions

b. a comparison of means in which one sample set had 10 measurements and the other had 30 measurements

c. a sample size of 5 a sample size of 50 sample

d. sets that differed in variance

e. a comparison of means in which one sample set had 37 measurements and the other had 41 measurements

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Answer:

The correct options are (c) and (d).

Step-by-step explanation:

The assumptions made before using a t-distribution for a hypothesis test are:

  1. The scale of the data should be continuous or ordinal.
  2. The sample selected should be a simple random sample.
  3. The data selected should follow a normal distribution or form a bell-shaped curve when plotted.
  4. The sample selected must be large enough so that when plotted a normal distribution curve is formed.
  5. Homogeneous variance exists so that the standard deviations of the samples are approximately equal.

A sample size of 5 a sample size of 50 sample will not be accurate for a t-test because on of the sample size is, 5.

This sample size is very small and when plotted will not follow a normal distribution.

The sets that differed in variance will not be accurate for a t-test because for using a t-test homogeneity of variances is assumed.

Thus, the correct options are (c) and (d).

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