Suppose we are about to draw a random sample of n values from a distribution where and . The shape of the distribution is not known, but it's not normal.Which of the following statements are true? There may be more than one correct statement; check all that are true. Question 10 options: a) If we sampled a million values from this distribution, and plotted a histogram of those values, that histogram would look approximately normal. b) If n is a very large number, then the sample mean would have a distribution that is approximately normal. c) The distribution of the sample mean will be very skewed if n < 30. d) The variance of the sample mean is 16.

Answered: we are about to draw a random sample of…

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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Suppose we are about to draw a random sample of n values from a distribution where and . The shape of the distribution is not known, but it's not normal.

Which of the following statements are true?

There may be more than one correct statement; check all that are true.

Question 10 options:

a)	If we sampled a million values from this distribution, and plotted a histogram of those values, that histogram would look approximately normal.

b)	If n is a very large number, then the sample mean would have a distribution that is approximately normal.

c)	The distribution of the sample mean will be very skewed if n < 30.

d)	The variance of the sample mean is 16.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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