#4 Which of the following statements is false? a.Increasing the sample size will always reduce the size of the sampling error when the sample mean is used to estimate the population mean. b.Increasing the sample size will reduce the potential for extreme sampling error. c.Sampling error can occur when the sample mean differs from the population mean due to the fact that the sample was not a perfect reflection of the population. d.There is no way to prevent sampling error short of taking a census of the entire population.#5 Which of the following regression output values is used in computing the variance inflation factors? a.The standard error of the estimate. b.The regression intercept value. c.The F critical value from the F distribution for the appropriate number of degrees of freedom. and the appropriate level of significance. d.The R-squared value.

4) Correct answer is option d. Sampling error can be prevented by taking larger sample size, randomisation, training of survey staff etc. 5) Correct answer is option d. VIF(variance inflation factor)=1/R-squared

Answered: Which of the following regression…

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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#4 Which of the following statements is false?

	a.	Increasing the sample size will always reduce the size of the sampling error when the sample mean is used to estimate the population mean.
	b.	Increasing the sample size will reduce the potential for extreme sampling error.
	c.	Sampling error can occur when the sample mean differs from the population mean due to the fact that the sample was not a perfect reflection of the population.
	d.	There is no way to prevent sampling error short of taking a census of the entire population.

#5 Which of the following regression output values is used in computing the variance inflation factors?

	a.	The standard error of the estimate.
	b.	The regression intercept value.
	c.	The F critical value from the F distribution for the appropriate number of degrees of freedom. and the appropriate level of significance.
	d.	The R-squared value.

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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