The most customers have a credit balance within this range. The relationship between the variables Income and Size is illustrated in the following scatter plot: It is clear from the scatter plot that no relationship exists between size and income. The points are scattered with no pattern. The relationship between the variables Income and Credit Balance is illustrated in the following scatter plot: There is a clear and definite relationship between the two variables, as shown in the scatter plot. There is a linear positive relationship between Income and Credit Balance variables.

Where income increases. Credit balance also increases. The relationship between the variables Years and Credit Balance is illustrated in the There is no clear relationship between the two variables in the scatter plot. The points are in no specific pattern, suggesting that there is no significant correlation between the variables years and credit balance. It can be concluded that some variables such as Income are strongly related to the credit balance of AS DAVIS department store customers. Several other variables appear to be unrelated. PART B: Hypothesis Testing and Confidence Intervals

Order nowI _a- The average (mean) annual income was less than $50,000 I found the average (mean) income to be $43, 740, with a standard deviation of 514,640 According to the hypothesis test (see appendix), the calculated test statistic of -3. 0236 does fall in the rejection region of z<-l . 645 therefore can reject the null hypothesis and say there is sufficient evidence to indicate or $50,000. The p-value of 0. 001 (see appendix for data), supports the rejection of the null hypothesis since the p value is less than a=buff. Based on the confidence interval, we can be 95% certain that the average income lies between -b.

The true population proportion of customers who live in an urban area exceeds 40% Of those surveyed, 22 out of 50 customers live in an urban area. The customers living in an urban area is equivalent to or 0. 440. This is my point estimate for p. According to the statistical analysis found in appendix a, we would not reject the hypothesis Ho= There is insufficient evidence to conclude the true population of customers who live in urban areas is greater than 40%. The p-value of 0. 440 (see appendix for data), supports the failure to reject the null hypothesis since the p value is more than 0-0. 5. Based on the confidence interval, we can be certain that the average number of customers who live in an urban area lies between 1 . C- The average (mean) number of years lived in the current home is less than 13 years The average number of years in the current home, according to the data, is 12 260 years with a standard deviation of 5086 years, The test statistic calculations found in the appendix, indicate that there is insufficient evidence to indicate that the average number of years lived in the current home is less than 13 years.