To: Boris Johns, Director of analytics
Sub: Data analysis
This is to inform you that I am replying to your previous email by attaching the summary of the data analysis performed in the Excel workbook.
This analysis is about the data set of the customers that show the saving and spending details of a buyer. Different variables consider for this analysis include total spending of a buyer, credit card usage, age bands, and eating out expenses.
1. In this question, the purpose is to determine the confidence interval for total expenses incurred by the customers using a 95% interval. The average spending of a customer is $4354 with a confidence interval of 19.
2. Another one is to identify the changes in the number of credit cards held by a user among the five categories of the cards. The results shows that the majority of the users do not have credit cards as they use other way of payment while shopping.
3. This question aims to spot the difference between the confidence intervals of eating outside expenses about the age groups. The results say that the eat out spending of a customer gets changes with the different age groups. Young age group customer prefers to eat outside as compared to old age one.
4. This question has categorized into three segments that are about the relationship between the income of an individual with savings, eat out expenses, and grocery expenses.
a) There is a negative relationship between monthly income and the monthly savings as the proportion of income bis higher than the savings. This shows that the customer’s spending is higher than its savings.
b) There is a positive relation among the monthly income and eat out expenses as income is higher than the eat out spending. But saving is also so this shows that a customer spends on other things as well.
c) Similarly, to the above analysis, this shows an apt balance among the grocery expenses and the monthly income. But the expenses spent on the groceries are higher than the eat out spending.
5. Again, this question has divided into three categories to show the relationship between the income and the age group of the customers.
a) This is about the probability of the income of the customers falls under different age groups exceeds the income of $4500. Customers fall under the age group of 70-75 have income that exceeds the $4500.
b) Another question is to enquire the proportion of the income of different age bands is less than $3500. Again, customers who lie in the age band of 70-75 have 0.4 probability of income having less than $3500. This shows that the rest of the other age groups have income less than $3500.
c) This is to determine the income of all the customers coming from different age bands. Out of everyone, the 40-45 age group customer consists of the highest income value than compared to another one.
a) Lastly, this says that the average total spending across different age bands is higher than $4200. The results show that the average spending of the customers is $4354 which is higher than $4200.
b) Now, the question is to know the proportion of the customers belongs to different age groups have fewer people than compare to one-fourth of the total count. The 25% of total count is 50, people are there in the age groups that is less than this count.
It is articulated from the analysis that the monthly income of all the customers is good and higher but proportionately savings are not up to the mark. The average spending is the same as the average income. So, this is not an apt case to generate enough savings when spending and income are on the same level.