Determine if the statements below are true or false. For each false statement, suggest an alternative wording to make it a true statement.As the degrees of freedom increases, the mean of the chi-square distribution increases.If you found chi2 = 10 with df = 5 you would fail to reject H0 at the 5% significance level When finding the p-value of a chi-square test, we always shade the tail areas in both tails.4. As the degrees of freedom increases, the variability of the chi-square distribution decreases.

1)True, As the degrees of freedom increases, the mean of the chi-square distribution increases. The mean of a chi-square distribution is its degrees of freedom.2) True, the critical value at 5% of the level of significance at DF=5 is 11.07 >10. Therefore, it's fail to reject the null hypothesis.3) False, When finding the p-value of a chi-square test, we always shade the tail area in one tail as squared term involved consider as a positive.4)True, AS DF of chi-square distribution increases it becomes less skewed and goes to normal distribution.

Answered: Determine if the statements below are…

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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Determine if the statements below are true or false. For each false statement, suggest an alternative wording to make it a true statement.

As the degrees of freedom increases, the mean of the chi-square distribution increases.
If you found chi2 = 10 with df = 5 you would fail to reject H0 at the 5% significance level
When finding the p-value of a chi-square test, we always shade the tail areas in both tails.

4. As the degrees of freedom increases, the variability of the chi-square distribution decreases.

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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