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Population data: 2,3,5,5,7,8

Part (a): Find the mean, μ, of the variable.

Part (b): For each of the possible sample sizes, construct a table similar to Table 7.2on the page 293and draw a dotplot for the sampling for the sampling distribution of the sample mean similar to Fig 7.1on page 293.

Part (c): Construct a graph similar to Fig 7.3and interpret your results.

Part (d): For each of the possible sample sizes, find the probability that the sample mean will equal the population mean.

Part (e): For each of the possible sample sizes, find the probability that the sampling error made in estimating the population mean by the sample mean will be 0.5or less, that is, that the absolute value of the difference between the sample mean and the population mean is at most0.5.

Short Answer

Expert verified

Part (a): The mean μis 5.

Part (b): When n=1,

When localid="1652599358621" n=2,

When localid="1652599361707" n=3,

When localid="1652599369696" n=4,

When localid="1652599366135" n=5,

When localid="1652599373256" n=6,


Part (c): The dot plot is given below,

Part (d): The probability that the sample mean will equal the population mean are 13,15,15,15,13,1.

Part (e): The probability that the sampling error made in estimating the population are13,13,25,35,23,1.

Step by step solution

01

Part (a) Step 1. Given information

Consider the given question,

The population data is2,3,5,5,7,8.

02

Part (a) Step 2. Find the mean of the variable.

The mean μis given below,

μ=xiN=2+3+5+5+7+86=306=5

03

Part (b) Step 1. Construct a table for n=1,2,3.

For each of the possible sample sizes, we construct a table.

If the sample size taken n=1,

If the sample size taken n=2,

If the sample size taken n=3,

04

Part (b) Step 2. Construct a table for n=4,5,6.

If the sample size taken n=4,

If the sample size taken n=5,

If the sample size taken n=6,

05

Part (c) Step 1. Construct the dot plot.

We will construct the dot plot for the sampling distribution of the sample mean.

To construct dot plot for the sampling distribution of the sample mean,

06

Part (d) Step 1. Find the probability that the sample mean will equal the population mean.

We can observe that from the dot plot there is two dot corresponding to μ=5 when nis 1.

Hence, the probability that sample mean will be equal to population mean=26=13

Similarly, the probability that sample mean will be equal to population mean when n is 2is =315=15(As there are data-custom-editor="chemistry" 3dots corresponding μ=5)

The probability that sample mean will be equal to population mean when n is 3is =420=15(As there are no dots corresponding μ=5)

We can observe that from the dot plot there is one dot corresponding to μ=5 when n is data-custom-editor="chemistry" 4.

The probability that sample mean will be equal to population mean when n is 4is =315=15(As there are 3dots corresponding μ=5)

The probability that sample mean will be equal to population mean when n is 5is 26=13.

The probability that sample mean will be equal to population mean forn=6is1.

07

Part (e) Step 1. Find the probability that sampling error made in estimating the population mean.

Number of dots within 0.5or less of μ=5is 2out of 6 when nis 1.

Hence, the probability that xwill be within 0.5or less of μis 26=13.

Number of dots within 0.5or less of μis 5out of 15 when nis 2.

Hence, the probability that xwill be within 0.5or less of μis 515=13.

Number of dots within 0.5or less of μis role="math" localid="1652598843137" 8out of 20 when n is 3.

Hence, the probability that xwill be within 0.5or less of μis 820=25,

Number of dots within 0.5or less of μis 9out of 15 when nis 4.

Hence, the probability that xwill be within 0.5or less of μis 915=35.

Number of dots within 0.5or less of μis 4out of 6 when n is 5.

Hence, the probability that xwill be within 0.5or less of μis 46=23.

Number of dots within data-custom-editor="chemistry" 0.5or less of μis 1out of 1 when n is 6.

Hence, the probability that xwill be within 0.5or less ofμis11=1.

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A variable of a population is normally distribution with mean μand standard deviation σ.

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