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Which of the following is not a property of the student t distribution? The underlying population of individual observations is assumed to be normally distributed with unknown population mean u and unknown population standard deviation o. The size of the underlying population is generally not relevant unless it is very small. If it is bell shaped (normal) then the assumption is met and doesn't need discussion. Random sampling is assumed, but that is a completely separate assumption from normality. The mean for the Student's t-distribution is zero and the distribution is symmetric about zero. The graph for the Student's t-distribution is similar to the standard normal curve. The graph for the Student's t-distribution is same as the standard normal curve. The Student's t-distribution has more probability in its tails than the standard normal distribution because the spread of the t-distribution is greater than the spread of the standard normal. So the graph of the Student's t-distribution will be thicker in the tails and shorter in the center than the graph of the standard normal distribution. The exact shape of the Student's t-distribution depends on the degrees of freedom. As the degrees of freedom increases, the graph of Student's t-distribution becomes more like the graph of the standard normal distribution.

Which of the following is not a property of the student t distribution? The underlying population of individual observations is assumed to be normally distributed with unknown population mean u and unknown population standard deviation o. The size of the underlying population is generally not relevant unless it is very small. If it is bell shaped (normal) then the assumption is met and doesn't need discussion. Random sampling is assumed, but that is a completely separate assumption from normality. The mean for the Student's t-distribution is zero and the distribution is symmetric about zero. The graph for the Student's t-distribution is similar to the standard normal curve. The graph for the Student's t-distribution is same as the standard normal curve. The Student's t-distribution has more probability in its tails than the standard normal distribution because the spread of the t-distribution is greater than the spread of the standard normal. So the graph of the Student's t-distribution will be thicker in the tails and shorter in the center than the graph of the standard normal distribution. The exact shape of the Student's t-distribution depends on the degrees of freedom. As the degrees of freedom increases, the graph of Student's t-distribution becomes more like the graph of the standard normal distribution.

MATLAB: An Introduction with Applications
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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Which of the following is not a property of the student t distribution? The underlying population of individual observations is assumed to be normally distributed with unknown population mean u and unknown population standard deviation o. The size of the underlying population is generally not relevant unless it is very smalI. If it is bell shaped (normal) then the assumption is met and doesn't need discussion. Random sampling is assumed, but that is a completely separate assumption from normality. O The mean for the Student's t-distribution is zero and the distribution is symmetric about zero. The graph for the Student's t-distribution is similar to the standard normal curve. The graph for the Student's t-distribution is same as the standard normal curve. The Student's t-distribution has more probability in its tails than the standard normal distribution because the spread of the t-distribution is greater than the spread of the standard normal. So the graph of the Student's t-distribution will be thicker in the tails and shorter in the center than the graph of the standard normal distribution. The exact shape of the Student's t-distribution depends on the degrees of freedom. As the degrees of freedom increases, the graph of Student's t-distribution becomes more like the graph of the standard normal distribution.
Transcribed Image Text:Which of the following is not a property of the student t distribution? The underlying population of individual observations is assumed to be normally distributed with unknown population mean u and unknown population standard deviation o. The size of the underlying population is generally not relevant unless it is very smalI. If it is bell shaped (normal) then the assumption is met and doesn't need discussion. Random sampling is assumed, but that is a completely separate assumption from normality. O The mean for the Student's t-distribution is zero and the distribution is symmetric about zero. The graph for the Student's t-distribution is similar to the standard normal curve. The graph for the Student's t-distribution is same as the standard normal curve. The Student's t-distribution has more probability in its tails than the standard normal distribution because the spread of the t-distribution is greater than the spread of the standard normal. So the graph of the Student's t-distribution will be thicker in the tails and shorter in the center than the graph of the standard normal distribution. The exact shape of the Student's t-distribution depends on the degrees of freedom. As the degrees of freedom increases, the graph of Student's t-distribution becomes more like the graph of the standard normal distribution.
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