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Paying for college College financial aid offices expect students to use summer earnings to help pay for college. But how large are these earnings? One large university studied this question by asking a random sample of 1296 students who had summer jobs how much they earned. The financial aid office separated the responses into two groups based on gender, so these can be viewed as independent samples. Here are the data in summary form:24

a. How can you tell from the summary statistics that the distribution of earnings in each group is strongly skewed to the right? The use of two-sample t procedures is still justified. Why?

b. Construct and interpret a 90% confidence interval for the difference between the true mean summer earnings of male and female students at this university.

c. Interpret the 90% confidence level in the context of this study

Short Answer

Expert verified

Part a) Because the sample sizes for 675 and 621 are both at least 30, we can continue to assume that the distribution is roughly normal.

Part b) There is 90%the confidence that the mean difference is between (412.69,635.58)

Part c) This can be interpreted from this context of the study.

Step by step solution

01

Part a) Step 1: Explanation

Because earnings cannot take on negative values and the standard deviation is almost the same as the mean, the distribution of earnings in each group is strongly skewed to the right. Because negative values are within two standard deviations of the mean and these values fall within the range of regular values for a symmetric distribution, the distribution must be strongly skewed. Because the sample sizes for 675and 621are both at least 30, we can continue to assume that the distribution is roughly normal.

02

Part b) Step 1: Given information

x1=1884.52x2=1360.39n1=376n2=621s1=1368.37s2=1037.46c=0.90

03

Part b) Step 2: Explanation

Confidence interval calculation:

Now we'll calculate the t-value, and to do so, we'll need to know how many degrees of freedom there are. As a result, the degree of liberty will be:

df=min(n1-1,n2-1)=min(675-1,621-1)=620>100df=100

Then the t-value will be as:

t*=1.660

As a result, the confidence interval will be:

localid="1654742561555" (x1-x2)-t2s12n1+s22n2=(1884.52-1360.39)-1.6601368.372675+1037.462621=412.69

(x1-x2)+t2s12n1+s22n2=(1884.52-1360.39)+1.6601368.372675+1037.462621=635.58

Therefore, we conclude that there is 90%the confidence that the mean difference is between (412.69,635.58)

04

Part c) Step 1: Explanation

The confidence interval of 90%means that 90%of all possible samples will have a confidence interval that contains the true population mean difference in earnings. This can be deduced based on the study's context.

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