1. Which of the following is consistent with the alternative hypothesis for the interaction of factors A and B in a two-factor analysis of variance? a. The mean differences between treatment conditions are what would be predicted from the overall main effects of Factors A and B. b. µA = µB c. µA ≠ µB d. The mean differences between treatment conditions are not what would be predicted from the overall main effects of Factors A and B. 2. A researcher uncovers that there is a significant interaction between the factor of marital status (i.e., married or non-married) and participant sex (i.e., male or female) regarding well-being among a sample with n = 6 participants in each condition. A researcher decides to compare the difference in well-being between married men and women. The MSwithin treatments from the original two-factor analysis is MSwithin treatments = 1.00. using the matrix below to test this simple main effect, which is the appropriate decision using an alpha level of α = .05? Participant Sex Males Females __________________________________________________________________ n = 6 n = 6 N = 12 M = 4 M = 5 G = 54 T = 24 T = 30 a. Fail to reject the null hypothesis and conclude there is not a significant difference in well-being between males and females who are not married. b. Fail to reject the null hypothesis and conclude there is not a significant difference in well-being between males and females who are married. c. Reject the null hypothesis and conclude there is a significant difference in well-being between males and females who are not married. d. Reject the null hypothesis and conclude there is a significant difference in well-being between males and females who are married.

1. Which of the following is consistent with the alternative hypothesis for the interaction of factors A and B in a two-factor analysis of variance? a. The mean differences between treatment conditions are what would be predicted from the overall main effects of Factors A and B. b. µA = µB c. µA ≠ µB d. The mean differences between treatment conditions are not what would be predicted from the overall main effects of Factors A and B. 2. A researcher uncovers that there is a significant interaction between the factor of marital status (i.e., married or non-married) and participant sex (i.e., male or female) regarding well-being among a sample with n = 6 participants in each condition. A researcher decides to compare the difference in well-being between married men and women. The MSwithin treatments from the original two-factor analysis is MSwithin treatments = 1.00. using the matrix below to test this simple main effect, which is the appropriate decision using an alpha level of α = .05? Participant Sex Males Females __________________________________________________________________ n = 6 n = 6 N = 12 M = 4 M = 5 G = 54 T = 24 T = 30 a. Fail to reject the null hypothesis and conclude there is not a significant difference in well-being between males and females who are not married. b. Fail to reject the null hypothesis and conclude there is not a significant difference in well-being between males and females who are married. c. Reject the null hypothesis and conclude there is a significant difference in well-being between males and females who are not married. d. Reject the null hypothesis and conclude there is a significant difference in well-being between males and females who are married.

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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Question

1. Which of the following is consistent with the alternative hypothesis for the interaction of factors A and B in a two-factor analysis of variance?

	a.	The mean differences between treatment conditions are what would be predicted from the overall main effects of Factors A and B.
	b.	µ_A = µ_B
	c.	µ_A ≠ µ_B
	d.	The mean differences between treatment conditions are not what would be predicted from the overall main effects of Factors A and B.

2. A researcher uncovers that there is a significant interaction between the factor of marital status (i.e., married or non-married) and participant sex (i.e., male or female) regarding well-being among a sample with n = 6 participants in each condition. A researcher decides to compare the difference in well-being between married men and women. The MS_{within treatments} from the original two-factor analysis is MS_{within treatments} = 1.00. using the matrix below to test this simple main effect, which is the appropriate decision using an alpha level of α = .05?

Participant Sex

Males Females

__________________________________________________________________

n = 6 n = 6 N = 12

M = 4 M = 5 G = 54

T = 24 T = 30

	a.	Fail to reject the null hypothesis and conclude there is not a significant difference in well-being between males and females who are not married.
	b.	Fail to reject the null hypothesis and conclude there is not a significant difference in well-being between males and females who are married.
	c.	Reject the null hypothesis and conclude there is a significant difference in well-being between males and females who are not married.
	d.	Reject the null hypothesis and conclude there is a significant difference in well-being between males and females who are married.

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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