Let's examine the méan of thế humbers 1, 2, 3, 4, 5, 6,7, and 8 by drawing samples from these values, calculating the mean of each sample, and then considering the sampling distribution of the mean. To do this, suppose you perform an experiment in which you roll an eight-sided die two times (or equivalently, roll two eight-sided dice one time) and calculate the mean of your sample. Remember that your population is the numbers 1, 2, 3, 4, 5, 6, 7, and 8. The true mean (µ) of the numbers 1, 2, 3, 4, 5, 6, 7, and 8 is , and the true standard deviation (o) is The number of possible different samples (each of size n = 2) is the number of possibilities on the first roll (8) times the number of possibilities on the second roll (also 8), or 8(8) = 64. If you collected all of these possible samples, the mean of your sampling distribution of means (PM) would equal v , and the standard deviation of your sampling distribution of means (that is, the standard error or oM) would be The following chart shows the sampling distribution of the mean (M) for your experiment. Suppose you do this experiment once (that is, you roll the die two times). Use the chart to determine the probability that the mean of your two rolls is equal to the true mean, or P(M = H), is - The probability that the mean of your two rolls is greater than 1.5, or P(M > 1.5), is ▼
Let's examine the méan of thế humbers 1, 2, 3, 4, 5, 6,7, and 8 by drawing samples from these values, calculating the mean of each sample, and then considering the sampling distribution of the mean. To do this, suppose you perform an experiment in which you roll an eight-sided die two times (or equivalently, roll two eight-sided dice one time) and calculate the mean of your sample. Remember that your population is the numbers 1, 2, 3, 4, 5, 6, 7, and 8. The true mean (µ) of the numbers 1, 2, 3, 4, 5, 6, 7, and 8 is , and the true standard deviation (o) is The number of possible different samples (each of size n = 2) is the number of possibilities on the first roll (8) times the number of possibilities on the second roll (also 8), or 8(8) = 64. If you collected all of these possible samples, the mean of your sampling distribution of means (PM) would equal v , and the standard deviation of your sampling distribution of means (that is, the standard error or oM) would be The following chart shows the sampling distribution of the mean (M) for your experiment. Suppose you do this experiment once (that is, you roll the die two times). Use the chart to determine the probability that the mean of your two rolls is equal to the true mean, or P(M = H), is - The probability that the mean of your two rolls is greater than 1.5, or P(M > 1.5), is ▼
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:Let's examine the mean of the numbers 1, 2, 3, 4, 5, 6, 7, and 8 by drawing samples from these values, calculating the mean of each sample, and
then considering the sampling distribution of the mean. To do this, suppose you perform an experiment in which you roll an eight-sided die two times
(or equivalently, roll two eight-sided dice one time) and calculate the mean of your sample. Remember that your population is the numbers 1, 2, 3, 4,
5, 6, 7, and 8.
The true mean (µ) of the numbers 1, 2, 3, 4, 5, 6, 7, and 8 is , and the true standard deviation (o) is
The number of possible different samples (each of size n = 2) is the number of possibilities on the first roll (8) times the number of possibilities on the
second roll (also 8), or 8(8) = 64. If you collected all of these possible samples, the mean of your sampling distribution of means (µM) would equal
and the standard deviation of your sampling distribution of means (that is, the standard error or ɑm) would be
The following chart shows the sampling distribution of the mean (M) for your experiment. Suppose you do this experiment once (that is, you roll the
die two times). Use the chart to determine the probability that the mean of your two rolls is equal to the true mean, or P(M = µ), is ▼ . The
probability that the mean of your two rolls is greater than 1.5, or P(M > 1.5), is
8
7-
1.0 1.5 2.0 2.5 3.0 3.5 4.0
4.5 5.0 5.5 6.0
6.5 7.0 7.5 8.0
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