Use R to solve the problem

The csv file and description needed is at

https://gofile.io/d/c5vSna

1. Do a quick EDA of the adherence time and weight loss variables. Describe the distributions of each variable, including the existence of outliers, if any.
2. 2.Create a scatterplot of weight loss () on adherence time (). Describe the relationship. Identify any potential outliers that could be influential in a linear regression, if any.
3. Run a linear regression of weight loss on adherence time. Do not use any transformations or subsets of data.

a. Write out the regression equation.

b. Interpret the slope parameter in the context of the problem.

c. What is the standard error for regression? Interpret this value.

d. How much variability in weight loss can be explained by adherence time?

4.Conduct linear regression model diagnostics. Does it meet the assumptions for inference for linear regression?

5.ssuming assumptions are met

a. Conduct a hypothesis test for the claim that the population slope of weight loss on adherence is greater than zero. Write out the hypotheses and all pertinent numbers in your summary, including the decision and interpretation in the context of the problem.

b.Find the 99% confidence interval for mean weight loss when adherence is 5.75 (median adherence). Interpret the interval in the context of the problem.

c.Find the 99% prediction interval for the weight of a new, randomly chosen person when adherence is 5.75. Interpret the interval in the context of the problem.

6.Create a subset of the data that removes observation 37 (adherence level 9.25). Rerun the regression with this subset. Is observation 37 influential?