Question

Q10(9).Use R to complete the following. R code and R output is requested for solution. R markdown is recommended. Please keep you solution clear and easy to read. Unclear solution will not be graded. 0 for manual solution. You are given the data set 4.52, 1.02, 0.27, 10.38, 13.04, -4.10, 8.21, -0.64, 4.35, 2.74, 14.00, 16.05, 5.57, 19.23, 7.52, 7.01, -0.63, 2.78, 7.64, 0.10 and told that it is a simple random sample from some distribution. 1(3). Obtain a normal probability plot of the sample and comment on what you see. 2(4). Implement a t-test in R for 0:=5 vs :>5. Let =0.01 . 3(2). Use R to calculate the 99\% confidence interval for the population mean

Answer 1

To obtain a normal probability plot of the sample, use the 'qqnorm' function in R. Implement a t-test in R for 0:=5 vs :>5 using the 't.test' function. Use the 't.test' function in R to calculate the 99% confidence interval for the population mean.

Step-by-step explanation:

To obtain a normal probability plot of the sample, you can use the 'qqnorm' function in R. Here is the R code and R output:

data <- c(4.52, 1.02, 0.27, 10.38, 13.04, -4.10, 8.21, -0.64, 4.35, 2.74, 14.00, 16.05, 5.57, 19.23, 7.52, 7.01, -0.63, 2.78, 7.64, 0.10)

qqnorm(data)

A normal probability plot is a graphical tool used to assess whether a data set follows a normal distribution. In the output, if the points on the plot roughly form a straight line, it suggests that the data follows a normal distribution. Any deviations from a straight line may indicate departures from normality.

To implement a t-test in R for 0:=5 vs :>5, you can use the 't.test' function. Here is the R code and R output:

result <- t.test(data, mu = 5, alternative = 'greater')

To calculate the 99% confidence interval for the population mean in R, you can use the 't.test' function. Here is the R code and R output:

result <- t.test(data, conf.level = 0.99)