can somebody please help me answer Question 1(1-19) and copy r codes

After you set working directory where the physical copy of "credit.txt" is located, use the code read.table("credit.txt", stringsAsFactors = T) to import it to R and assign it to credit. Now answer the following questions:

1. (2 pts) What is the type of Rating variable? 2. (3 pts) Find five-number summary of Rating variable.

3. (4 pts) What is an appropriate plot to visualize the five-number summary? Visualize the five-number summary of Rating variable.

4. (6 pts) Find how many outliers we have in Rating variable. Provide your reasoning how you defined them as outliers.

5. (6 pts) Find a 95% confidence interval to estimate the population mean of credit rating and interpret the confidence interval.

6. (9 pts) Credit card company is interested in whether the population mean of credit rating is greater than 340. State the null and alternative hypothesis. Perform the hypothesis test. Compare the p-value to significance level (0.05) and make final decision. Make your final conclusion.

7. (2 pts) What is the type of Student variable?

8. (6 pts) Provide an appropriate visualization to compare whether there is a credit card rating difference between student and non-student. Describe your findings from the visualization.

9. (9 pts) Credit card company is interested in whether there is a difference in mean of credit rating between student and non-student. State the null and alternative hypothesis. Perform the hypothesis test. Compare the p-value to significance level (0.05) and make final decision. Make your final conclusion.

10. (2 pts) What is the type of Married variable?

11. (3 pts) Create a table object with Married variable.

12. (3 pts) Provide an appropriate visualization to summarize the Married variable.

13. (6 pts) Find a 95% confidence interval to estimate the population proportion of married customer and interpret the confidence interval.

14. (9 pts) Credit card company is interested in whether the population proportion of married customer is more than half. State the null and alternative hypothesis. Perform the hypothesis test. Compare the p-value to significance level (0.05) and make final decision. Make your final conclusion.

15. (3 pts) Draw the scatter plot with Income (x-axis) and Rating (y-axis) variable.

16. (6 pts) Calculate Pearson's correlation between Income and Rating variable. Provide your interpretation on the relationship between two variables.

17. (6 pts) Fit a simple linear regression model. Set Rating as response variable and Income as explanatory variable. Report the estimate of the slope coefficient and interpret the slope coefficient.

18. (6 pts) Fit a multiple linear regression model. Set Rating as response variable and Income and Student as explanatory variables. Find the predicted credit rating for a student whose income is 50.

19. (9 pts) Credit card company is interested in whether the mean Rating for three different Ethnicity of customers are different. State the null and alternative hypotheses. Perform the one-way ANOVA. Compare the p-value to significance level (0.05) and make your final conclusion

dataset file - https://drive.google.com/file/d/1UkoenRfFdEUHaF4HqwQm4TwVtva9faMR/view