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Variable life insurance return rates. Refer to the International Journal of Statistical Distributions (Vol. 1, 2015) study of a variable life insurance policy, Exercise 4.97 (p. 262). Recall that a ratio (x) of the rates of return on the investment for two consecutive years was shown to have a normal distribution, with =1.5, =0.2. Consider a random sample of 100 variable life insurance policies and letxrepresent the mean ratio for the sample.

a. Find E(x) and interpret its value.

b. Find Var(x).

c. Describe the shape of the sampling distribution ofx.

d. Find the z-score for the value x=1.52.

e. Find Px>1.52

f. Would your answers to parts a鈥揺 change if the rates (x) of return on the investment for two consecutive years was not normally distributed? Explain.

Short Answer

Expert verified

a. The mean ratio of the rates of return on the investment for two consecutive years for the sampling distribution of x is 1.5.

b. Variance ofsampling distribution of xis 0.0004.

c. The shape of the sampling distribution of x is normal.

d.The required z-score is 1.

e.Probability of x greater than 1.52 is 0.1587.

f. The answers in the parts a-e would not change if the rates were not normally distributed

Step by step solution

01

Given information

From the given problem, the distribution of X follows normal with mean=1.5 and a standard deviation=0.2

02

Calculating the mean of x

a.

From the central theorem, as the sample size is large the mean of the sample follows normal distribution with mean x= and variance 2n.

The mean of the sampling distribution of x is the population mean . That is,

x=

Ex=

Thus,

Ex=1.5

The mean ratio of the rates of return on the investment for two consecutive years for the sampling distribution of x is 1.5.

03

Calculating the variance of x 

b. From the given problem the sample size is n=100

Since,

Varx=2n

=0.22100=0.04100=0.0004

Thus,

Varx=0.0004

04

Describing the shape of sampling distribution

c.

From the central limit theorem as the sample size is large the mean of the sample follows normal distribution. The shape of the sampling distribution of x is normal.

05

Calculating the z-score

d.

Consider x=1.52

=1.5 and Varx=0.0004

The z-score is,

z=x-Varx

=1.52-1.50.0004=0.020.02=1

Thus, the required z-score is 1.

06

Calculating the probability 

e. Let,

Px>1.52=Px-Varx>1.52-1.50.0004=Pz>1=1-Pz<1=1-0.5+P0<z<1=1-0.5-0.3413=0.1587

Therefore, Probability of x greater than 1.52 is 0.1587.

07

Interpretation

f. The given sample size is 100, which is greater than 30. Thus, the distribution of sample mean x is approximately normal without considering the population distribution. Therefore, the Central limit theorem is relevant for the given data.

Thus, the answers in the parts a-e would not change if the rates were not normally distributed.

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Most popular questions from this chapter

Switching banks after a merger. Banks that merge with others to form 鈥渕ega-banks鈥 sometimes leave customers dissatisfied with the impersonal service. A poll by the Gallup Organization found 20% of retail customers switched banks after their banks merged with another. One year after the acquisition of First Fidelity by First Union, a random sample of 250 retail customers who had banked with First Fidelity were questioned. Letp^ be the proportion of those customers who switched their business from First Union to a different bank.

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The probability distribution shown here describes a population of measurements that can assume values of 0, 2, 4, and 6, each of which occurs with the same relative frequency:

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  2. Calculate the mean of each different sample listed in part a.
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Question: The standard deviation (or, as it is usually called, the standard error) of the sampling distribution for the sample mean, x , is equal to the standard deviation of the population from which the sample was selected, divided by the square root of the sample size. That is

X=n

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A=n3

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