Hypothesis testing

Please see attached file for full problem description and the data to do the hypothesis.

Please show all work and write the analysis.

Thanks

Quick Stab Collection Agency (QSCA), is a bill-collecting agency. The company specializes in collecting small accounts. The marketing department has just suggested that QSCA adopt the slogan "Under 60 days or your money back!!!!!" At the last staff meeting in which this slogan was proposed, the marketing department was asked how it arrived at the number 60. You found the reply unsatisfactory at best: "Well, uh, 60 sounded like a nice round number." Since you work as an accountant at QSCA, you look at account balances all of the time. In fact, you suspect that the number of days to collect the payment is related to the size of the bill. If this is the case, you may be able to estimate how quickly certain accounts are likely to be collected. You've taken a random sample of accounts closed out during the months of January through June. The data set includes the initial size of the account and the total number of days to collect payment in full. Because QSCA deals in both household and commercial accounts in about the same proportion, you've collected an equal number from both groups. The first 48 observations in the data set are residential accounts and the second 48 are commercial accounts.
Data file is attached
Variable Label
LATE Number of days payment is overdue.
BILL Dollar amount of the overdue bill.
1. What must you do during data preparation to enable you to compare commercial and household accounts?
2. Is the "60-day" money-back guarantee supported?

Managerial Dilemma:
Manager needs more information about customer's accounts that overdue.

Research Question:
Is there a difference in the "60-day" money back guarantee if the customer account is commercial or residential?

Hypothesis:
Null Hypothesis: µ≤60 days (There is no difference in the number of days over due accounts are collected for residential and commercial)

Alternative Hypothesis: µ>60 days( Commercial accounts take longer to collect than residential accounts)

Data Collection:
o The variables in the data are the number of days and the dollar amount of the bills.
o Discuss the mean, media, mode, standard deviation of all the days for the accounts for each customer.
 Residential
 Commercial

Statistical Analysis
o One-sided, two population testing will be used
o Discussed the significance level used and why we used this
o Include all the supportive numbers from the QUAC Utility.