A B E Now that you've started to breakdown and analyze the individuals surveyed by gender, age, and salary, you and the team would like to start analyzing some of the Credit Scores of those indivuals. You pull a subset of the customers and assume that the subset of data about Credit Scores is normally distributed. Use the info to the right to complete the z-table and answers the questions below. In this case, you will have to calcucate each z-score MANUALLY, since there is a random number generator active in the Excel. 1) What is the highest z-score and what does it mean? The highest z-score is Gianni Mullen with a z-score of 1.442. This high of a z-score means that Gianni 2) What is the lowest z-score and what does it mean? The lowest z-score is Wesley Mohamed with a z-score of -1.563. This low off a z-score means that Wesley 3) Is it safe to assume that this data is normal or near normally distributed? If not, explain why and cite specific reasons/support for that reason. Yes, it is safe to assume that the data is normally distributed due to all of the data within the problem being between -2 and 2. 4) Identify any customers near the mean and explain what that means/how you know this. Mia-Rose Walton and Owen Hook are the two customers that are near the mean, Mia-Rose has a 0.053 z-score and Owen has a z- score of 0.095. 5) Explain HOW you and your team may try to test and validate whether or not this subset of data could be generalized to the larger group and population. Salary Analysis Z-Scorinnikatelm