Question 2Which of the following was NOT a factor which led to the proliferation of life insurance?0 / 1 pointInsurance salespeopleIncreased life expectancyStatistical data on life expectancyNew sales pitches

Which of the following statements about the ‘Life Insurance’ section of the lecture material are TRUE:Life insurance policies that bundle a savings product together with death cover in one policy can be a good option for people who would like to make sure that they receive a payout at age 60 whether they live until 80 or die prematurely before the age of 60.Trauma insurance pays a lump-sum amount upon diagnosis of a serious illness, such as cancer. This could be a useful form of insurance if someone has a history of a particular type of cancer in their family.Question 8AnswerNeither of the statements are true (both are false)Only statement 1 is trueOnly statement 2 is trueBoth statements are true (neither are false)

Fill in the Blank QuestionFill in the blank question.When considering life insurance, you should consider present and sources of income.

Multiple Select QuestionSelect all that applyWhich of the following factors should be considered before buying life insurance?Multiple select question.net worthgroup life insurancepresent and future incomestock pricesoption market prices

An insurance company offers life insurance policies.What kind of questions do you think the expertsystem will ask in order to establish whether aninsurance policy would be issued to a user?

Context:We are interested in understanding the family characteristics that determine the amount of insurance purchased by a household. We have access to the following information from a survey of households who have purchased term life insurance:FACE: The amount that the insurance company will pay in the event of the death of the named insured. This serves as a measure of the quantity of insurance owned by the household.INCOME: The total annual income of the household.EDUCATION: The number of years of education of the head of the household.NUMHH: The number of household members.MARSTAT: The marital status of the respondent of the survey. It takes values: 1 for married, 2 for living with partner, 0 for other.GENDER: Gender of the survey respondent. It takes value 1 if female and 0 otherwise.Please find attached the dataset TermLife.csv.Complete the following 2 questions:a) Perform the following coding tasks in R:Import the dataset TermLife.Look at the structure of the dataset using the function str() and look at the summary of the each variable using the function summary().Filter the dataset for values of FACE strictly positive.Encode MARSTAT as a factor variable using the function factor().Model A: Perform a multiple linear regression with FACE as the response and INCOME, EDUCATION, NUMHH, MARSTAT and GENDER as the predictors. Use the function summary() to print the results.Model B: Perform a multiple linear regression with log(FACE) as the response and log(INCOME), EDUCATION, NUMHH, MARSTAT and GENDER as the predictors. Use the function summary() to print the results.b) Comment on the results of fitting models A and B, justifying your responses. In particular, discuss: What predictors appear to have a statistically significant relationship to the response for each model? How well do the models fit the data?Compare models A and B. Which model fits the data better?Share any other findings you may find interesting.