Task Assigned: Midterm Project •                              Conduct a descript

Task Assigned: Midterm Project •                              Conduct a descriptive analysis of the dataset “Midterm-Project-DataSet” including relevant graphs and tables, with a summary of the findings. What conclusions can be drawn from the descriptive analysis? (3 points) •                              Use appropriate diagrams to see if having an “Amazon prime” subscription influences membership in your company’s “loyalty” program. (2 points) •                              Display the stacked bar chart of the variable “NbReturns” with an overlay of the variable “Loyalty”, then draw conclusions. (2 points) •                              Determine the 95% confidence interval for the proportion π of customers with membership in the loyalty program among the entire population of the company’s customers. (1 point) •                              Perform the appropriate statistical test to compare the mean purchase values of customers who have membership in the “loyalty” program with those who do not have this membership. Is the test significant? (2 points) •                              Identify the factors whose relationship with purchase value is significant. For this question, you must: •                              a. Perform a linear regression by identifying the dependent variable and independent variables. Ignore the variable “MaritalStatus”. (2 points) •                              b. Provide the results table and discuss it. (2 points) •                              c. Diagnose the model by indicating violated assumptions. (2 points) •                              Identify the factors whose relationship with investment in Bitcoin is significant. For this question, you must: •                              a. Perform a linear regression by identifying the dependent variable and independent variables. Consider the variable “MaritalStatus”. (2 points) •                              b. Provide the results table and discuss it. (2 points) •                              c. Diagnose the model by indicating violated assumptions. (2 points) •                              Using RStudio, partition the dataset into a training set and a test set. Assume that the training set contains 80% of the records (randomly drawn). Evaluate the validity of the partition considering the variables “AmznPrime” and “NbReturns”. (3 points) Dataset Description: The dataset “Midterm-Project-DataSet” contains 503 records and 12 variables defined as follows: •                              Gender: the gender of the customer (M/F). •                              Age: the age of the customer. •                              Income: the monthly income of the customer. •                              StockInvestment: monthly investment of the customer in the stock market. •                              BitcoinInvestment: investment of the customer in Bitcoin. •                              NbReturns: number of times the customer returned an item after purchase. •                              Fuel: monthly amount (in dollars) spent on fuel purchase. •                              Mortgage: monthly mortgage payment. •                              PreviousPurchase: purchase value of month n. •                              PurchaseValue: purchase value of month n+1. •                              AmznPrime: does the customer have an “Amazon prime” subscription? •                              Loyalty: does the customer have membership in the company’s loyalty program? •                              MaritalStatus: the marital status of a customer (single, married, or divorced).