Questions: It is not reasonable to assume normality because of outliers. (e) Explain why the assumptions for the hypothesis test are satisfied even though the population is not normal. The assumptions are satisfied because (Choose one).

It is not reasonable to assume normality because of outliers. (e) Explain why the assumptions for the hypothesis test are satisfied even though the population is not normal. The assumptions are satisfied because (Choose one).
Transcript text: It is not reasonable to assume normality because of $\square$ outliers. (e) Explain why the assumptions for the hypothesis test are satisfied even though the population is not normal. The assumptions are satisfied because $\square$ (Choose one) .
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Solution

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Solution Steps

Step 1: Identify Outliers

The 'x' marks outside the boxplot's whiskers indicate two outliers.

Step 2: Reason for Non-Normality

The presence of these outliers suggests the data distribution is skewed and deviates from a normal distribution.

Final Answer

It is not reasonable to assume normality because of two outliers. The assumptions are satisfied because the sample size is large.

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