8. Using Minitab to illustrate the Central Linmit Theorem (CLT), the CLT tells us about the sampling distribution of the sample mean. With Minitab we can easily "sample" from a population with known properties ( µ,0 , shape). a. Our population consists of integer values X from 1 through 8, all equally likely P(x) = 1/8; x= 1, 2, 3, 4, 5, 6, 7, 8 Using methods from the beginning of Chapter 4 in the textbook, find u. Use your calculator to find u . What is the shape of this probability distribution? Does it Ở = 2.29 "look" Normal?

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#8. Using Minitab to illustrate the Central Limit Theorem (CLT), the CLT tells us about the
sampling distribution of the sample mean. With Minitab we can easily "sample" from a
population with known properties (4,0 , shape).
a. Our population consists of integer values X from 1 through 8, all equally likely
Р(x) 3D 1/8; х %3D
1, 2, 3, 4, 5, 6, 7, 8
Using methods from the beginning of Chapter 4 in the textbook, find u.
Use your calculator to find u. What is the shape of this probability distribution? Does it
o =2.29
"look" Normal?
b. Take a sample of size 3 from this population and compute the sample mean. Repeat this
process 1000 times.
Click on Calc > Random Data
Rows 1000
Store in columns C1-C3
Distribution Integer
Minimum 1
Maximum 8
Compute the mean of each sample (row) and store the sample means in C4.
Note: C4 has 1000 sample means each a sample of size n=3.
Click on Calc → Row Statistics
O Mean
Input Variables C1-C3
Store C4
Transcribed Image Text:#8. Using Minitab to illustrate the Central Limit Theorem (CLT), the CLT tells us about the sampling distribution of the sample mean. With Minitab we can easily "sample" from a population with known properties (4,0 , shape). a. Our population consists of integer values X from 1 through 8, all equally likely Р(x) 3D 1/8; х %3D 1, 2, 3, 4, 5, 6, 7, 8 Using methods from the beginning of Chapter 4 in the textbook, find u. Use your calculator to find u. What is the shape of this probability distribution? Does it o =2.29 "look" Normal? b. Take a sample of size 3 from this population and compute the sample mean. Repeat this process 1000 times. Click on Calc > Random Data Rows 1000 Store in columns C1-C3 Distribution Integer Minimum 1 Maximum 8 Compute the mean of each sample (row) and store the sample means in C4. Note: C4 has 1000 sample means each a sample of size n=3. Click on Calc → Row Statistics O Mean Input Variables C1-C3 Store C4
c. Compute the mean and stand. dev. of your 1000 sample means.
Click on Stat = Basic Statistics = Display Descriptive Statistics
Variable C4
Statistics check only mean and standard deviation
What did you expect for the mean of the sample means?
What did you get?
What did you expect for the stand. dev. of the sample means?
What did you get?
Briefly explain, how this illustrates 2 parts of the CLT.
d. Draw a histogram of your sample means.
Click on Graph Histogram Simple
Graph Variable C4
Discuss how this graph illustrates the CLT.
(Note: For #8 the sample size n=3 is less than 30)
Transcribed Image Text:c. Compute the mean and stand. dev. of your 1000 sample means. Click on Stat = Basic Statistics = Display Descriptive Statistics Variable C4 Statistics check only mean and standard deviation What did you expect for the mean of the sample means? What did you get? What did you expect for the stand. dev. of the sample means? What did you get? Briefly explain, how this illustrates 2 parts of the CLT. d. Draw a histogram of your sample means. Click on Graph Histogram Simple Graph Variable C4 Discuss how this graph illustrates the CLT. (Note: For #8 the sample size n=3 is less than 30)
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