- Imagine that you roll a single, fair, six-sided die once. Define the random variable X, to be the number of dots (pips) on the upward face. Complete the probability distribution table for X. P(x) 1 5 6.

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4. Now imagine that you roll two dice, one red and one green. What are the
possible sample means that you could have? Complete the following table,
entering the sample mean number of pips for each of the 36 possible outcomes.
Some have been done for you.
MAT 120 - Introduction to Statistics
ACTIVITY #10: Central Limit Theorem.
In this activity, we investigate the sampling distribution of the sample mean, X
1
3
4
5
6
1
1. Imagine that you roll a single, fair, six-sided die once. Define the random
variable X, to be the number of dots (pips) on the upward face, Complete the
probability distribution table for X.
2
1.5
3
2.5
5
6
P(x)
1
5. Using the 36 sample means found in #4, complete the probability distribution
table for X, the mean number of pips on the faces when 2 dice are rolled.
2
3
4
5
P(x)
6
1
1.5
2
2. Sketch the probability histogram for X below. Let the x-axis be the OUTCOME
and let the y-axis be the PROBABILITY,
2.5
3
3.5
4
4.5
5
5.5
6.
Sketch the probability histogram for X below. Compare your results with those
in #2.
3. Determine the mean and standard deviation for X. As a reminder, you determine
the mean of a discrete probability distribution using u =xP(x) and the
standard deviation is found most simply using the formula
o =Ex' P(x) - u? (see.page 322).
Transcribed Image Text:4. Now imagine that you roll two dice, one red and one green. What are the possible sample means that you could have? Complete the following table, entering the sample mean number of pips for each of the 36 possible outcomes. Some have been done for you. MAT 120 - Introduction to Statistics ACTIVITY #10: Central Limit Theorem. In this activity, we investigate the sampling distribution of the sample mean, X 1 3 4 5 6 1 1. Imagine that you roll a single, fair, six-sided die once. Define the random variable X, to be the number of dots (pips) on the upward face, Complete the probability distribution table for X. 2 1.5 3 2.5 5 6 P(x) 1 5. Using the 36 sample means found in #4, complete the probability distribution table for X, the mean number of pips on the faces when 2 dice are rolled. 2 3 4 5 P(x) 6 1 1.5 2 2. Sketch the probability histogram for X below. Let the x-axis be the OUTCOME and let the y-axis be the PROBABILITY, 2.5 3 3.5 4 4.5 5 5.5 6. Sketch the probability histogram for X below. Compare your results with those in #2. 3. Determine the mean and standard deviation for X. As a reminder, you determine the mean of a discrete probability distribution using u =xP(x) and the standard deviation is found most simply using the formula o =Ex' P(x) - u? (see.page 322).
9. If we were to repeat the process in # 1-6 for n=3 dice, there would be 216
possible outcomes (why?); we would find the mean of the X distribution equal
to 3.5 and the standard deviation equal to 1.71//3. The graph of the
7. Compute the mean and standard deviation of the distribution in #5.
distribution is shown below.
Histogram of means, n=3 dice
30
25
20
15
10
8. Verify that your results in #3 and #7 agree with the information in the text on
page 401, "The mean of the sampling distribution of the sample mean is equal to
the mean of the underlying population, and the standard deviation of the
sampling distribution of the sample mean is
1
1.33 1.67 2 2.33 2.67 3 3.33 3.67
4 4.33 4.67 5 5.33 5.67 6
%, regardless of the size of the
Explain how the dice example illustrates the Central Limit Theorem, cited on
page 401 of the text:
sample."
The Central Limit Theorem
Regardless of the shape of the underlying population, the sampling distribution of
x becomes approximately normal as the sample size, n, increases.
Transcribed Image Text:9. If we were to repeat the process in # 1-6 for n=3 dice, there would be 216 possible outcomes (why?); we would find the mean of the X distribution equal to 3.5 and the standard deviation equal to 1.71//3. The graph of the 7. Compute the mean and standard deviation of the distribution in #5. distribution is shown below. Histogram of means, n=3 dice 30 25 20 15 10 8. Verify that your results in #3 and #7 agree with the information in the text on page 401, "The mean of the sampling distribution of the sample mean is equal to the mean of the underlying population, and the standard deviation of the sampling distribution of the sample mean is 1 1.33 1.67 2 2.33 2.67 3 3.33 3.67 4 4.33 4.67 5 5.33 5.67 6 %, regardless of the size of the Explain how the dice example illustrates the Central Limit Theorem, cited on page 401 of the text: sample." The Central Limit Theorem Regardless of the shape of the underlying population, the sampling distribution of x becomes approximately normal as the sample size, n, increases.
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