AJ Davis is a department store chain, which has many credit customers and want to find out more information about these customers. AJ Davis has complied a sample of 50 credit customers with data selected in the following variables: Location, Income (in $1,000’s), Size (Number of people living in the household), Years (number of years the customer has lived in the current location), and Credit Balance (customers current credit card balance on the store’s credit car, in $).

The manager at AJ Davis has speculated the following: a. The average (mean) annual income was less than $50,000. b. The true population proportion of customers who live in an urban area exceeds 40% c. The average (mean) number of years lived in the current home is less than 13 years d. The average (mean) credit balance for suburban customers is more than $4300

I will analyze the speculated data listed above by performing hypothesis test for each of the above situations (using the Seven elements of a Test Hypothesis with a=.05) in order to see if there is evidence to support my manager’s beliefs in each case (a-d), explain my conclusion in simple terms, compute the p-value with the interpretation, follow up with computing 95% confidence intervals for each of the variables described in a. to d. along with interpreting these intervals. This paper will also include an Appendix with all the steps in hypothesis testing, as well as the confidence intervals and Minitab output

In order to understand how hypothesis testing is done it is important that you know the elements of the Test of Hypothesis, and what each step means.

The Seven elements of a Test of Hypothesis are:

1. Null Hypothesis - A theory about the specific values of one or more population parameters. The theory generally represents the status quo, and we accept it until proven false.

2. Alternative (research) hypothesis (Ha)- A theory about the specific values of one or more