Question

How can you resolve this case study by using R studio from chapter 10 , book business statistics written by Jaggia/Kelly third edition.can you please resolve for me

Case study 10.1

Chad perrone is a financial analyst Boston studying the annual return data for the health and information technology industries. He randomly samples 20 firms in each industry and notes each firm’s annual return. A portion of the data is shown in the accompanying table.

Data for Case Study 10.1 Annual Returns (in percent) for Firms in Health and Information Technology Industries

Health	Information Technology
10.29	4.77
32.17	1.14
. . .	. . .
13.21	22.61

In a report, use the sample information to

1. Provide descriptive statistic and comment on the reward and risk in each industry.
2. Determine whether the average returns in each industry differ at the 5% significance level. Assume that the population variances are not equal

Answer 1

The R output is:

The R code is:

Health <- c(10.29,32.17,34.27,10.57,20.27,31.43,15.4,0.88,17.85,28.98,6.49,28.73,8.17,14.83,12.89,23.51,29.14,4.42,34.67,13.21)
IT <- c(4.77,1.14,-12.72,48.1,6.69,11.65,53.28,-10.41,50.88,48.63,24.67,23.88,-14.8,6.94,29.52,43.42,23.56,-6.62,45.55,22.61)
summary(Health)
summary(IT)
t.test(Health, IT, var.equal = FALSE, alternative = "two.sided")

Summary statistics shows that the reward in IT industries is greater than health industries and IT industries have more variable rewards and risk in comparison to health industries.

The hypothesis being tested is:

H0: µ1 = µ2

H1: µ1 ≠ µ2

The p-value is 0.8432.

Since the p-value (0.8432) is greater than the significance level (0.05), we cannot reject the null hypothesis.

Therefore, we cannot conclude that the average returns in each industry differ at the 5% significance level.

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