Question

Write the code on Python:- Enter the number of adults (1-2): 2. Enter the number of children (0+): 4. Enter the age of child 1: 12. Enter the age of child 2: 13. Enter the age of child 3: 2. Enter the age of child 4: 5. What tier of cover would you like? [B]asic/[S]ilver/[G]old: s. Your premium is: $ 111.25 per week, OR $ 483.38 per month, OR $5800.57 per annum. Do you need another quote (y/n)? y. Enter the number of adults (1-2): 1. Enter the number of children (0+): 0. What tier of cover would you like? [B]asic/[S]ilver/[G]old: g. Your premium is: $30.00 per week, OR $130.35 per month, OR $1564.20 per annum. Do you need another quote (y/n)? n.

Answer 1

The question deals with Python programming for insurance premium calculations but primarily involves concepts of actuarial science, including statistical analysis and probability, to determine insurance costs and fair premiums based on risk factors.

Step-by-step explanation:

Insurance Premium Calculations in Python

It appears we are looking at an example where Python code is needed to calculate insurance premiums based on a variety of inputs including the number of adults, children, their ages, and the desired tier of cover. However, the provided scenarios involve concepts of probability, statistics, and risk assessment, commonly found in actuarial science and mathematics, especially when considering the cost of auto insurance for teenagers or the estimation of life insurance premiums for individuals based on their health history and risk factors. These examples highlight the important role that statistical analysis and probability play in the insurance industry and how such data informs the pricing of insurance premiums.

When considering the means and standard deviations given for the cost of auto insurance for teenage boys and girls, a hypothesis test can be applied to determine if there is a significant difference. Calculating the actuarially fair premium requires understanding the expected loss, which is the product of the probability of an event and its financial consequence. This concept is illustrated when dividing the 50-year-old men into groups with and without a family history of cancer and then estimating the fair premium based on their respective mortality risks.

Finally, the provided tax brackets and income segments highlight the progressive nature of tax rates, which is a key principle in personal and business finance when analyzing after-tax incomes and expenses.