Insurance is an integral part of peoples' life. It is a flourishing industry from a business point of view. This industry is mainly divided into two sub sectors namely life insurance and general insurance. Life insurance companies are keenly interested in predicting how long their customers will live, because their premium and profitability depends on such numbers. An actuary for one insurance company gathered data from 100 recently deceased clients. He recorded the age at death, ages at death of their mothers and fathers, number of years of employment and gender. Gather 80 observation (16-95) from the given data set.

https://docs.google.com/spreadsheets/d/13RI1z6PlS_u9TLw3GxDtH77LNj9cbf15/edit?usp=sharing&ouid=114495525509871115605&rtpof=true&sd=true

1. Perform descriptive statistical analysis in excel and prepare a table with following descriptive measures for quantitative variables in your data set. Mean, median, mode, variance, standard deviation, skewness, kurtosis, coefficient of variation.

2. Briefly comment on the descriptive statistics in the question 1 and explain the nature of the distribution (whether the variables are normally distributed or not) of those variables. Use graphs where necessary.

3. Construct suitable graphs to represent the relationship between dependent variables and each quantitative independent variable in your data set.

4. Construct a suitable graph to describe the gender composition of the clients in your sample.

5. Based on the data set you extracted, perform a regression analysis and correlation analysis, and answer the questions given below. a. Interpret the meaning of all the coefficients in the regression equation. b. Interpret the calculated coefficient of determination and the standard error of the estimate c. At 5% significance level, test the overall model significance. d. At 5% significance level, assess the significance of independent variables in the model. e. Based on the correlation coefficients in the correlation output, assess the correlation between explanatory variables and check the possibility of multicollinearity.

6. Assuming that you are the actuary, help this insurance company to make policy decisions on insurance premiums. Your suggestions should be based on the above findings. You can propose to them to gather more evidence if there are important variables omitted in the above.