R Programming Assignment -

Instructions: Please submit both R script and word document with final answers (where appropriate).

Question 1 - Download the seasonal_data.csv data set. Create an R script that addresses the following:

Show a table of average sales by month.

Show a table of average sales by year.

Show a table that lists all years, the month that contained the maximum sales amount for the entire year, and the corresponding amount.

Assume the following quarters: Q1 (Jan, Feb, Mar), Q2 (April, May, June), Q3 (July, Aug, Sep), and Q4 (Oct, Nov, Dec). Using data visualization to support your points, describe the variation in sales by quarter.

Question 2 - Download the bank_customers.csv data set. Create an R script that addresses the following:

Recode Education column from numeric to character where 1 represents "Undergrad," 2 represents "Graduate," and 3 represents "Advanced."

Make Education an ordered factor variable.

Create an Income_level column with "Low" representing below $50,000, "Medium" representing $50,000 - $150,000 inclusive and "High" representing above $150,000.

Create a facet wrap bar chart that shows the Average Age for each Income_level that is wrapped by Education.

Create a scatter plot of average spending on credit cards (CCAvg) vs. income. CCavg should be the y-variable while income should be the x-variable. Use different point colors to represent the varying levels of education.

Create 3 linear regression models of CCavg (y) vs. Income (x) for each level of education. Show the regression coefficients of each model.

What was the customer ID and corresponding residual value of the customer with the most overestimated CCavg?

What was the customer ID and corresponding residual value of the customer with the most underestimated CCavg?

How many customers had a predicted value within 10% (plus or minus) from their actual value?