Research Methods for the Behavioral Sciences (MindTap Course List)

6th Edition

ISBN: 9781337613316

Author: Frederick J Gravetter, Lori-Ann B. Forzano

Publisher: Cengage Learning

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Textbook Question

Chapter 11, Problem 10E

A two-factor analysis of variance is used to evaluate the significance of the mean differences for the two-factor research study shown in the following table. The study is evaluating the effects of sugary versus nonsugary snacks on the activity level of preschool children. Identify the three F-ratios and, using the following data from a 2 × 2 design, identify the means (or mean differences) that are compared by each F-ratio.

	Before Snack	After Snack
Sugary snack	M = 20	M = 24	M = 22
Nonsugary Snack	M = 22	M = 26	M = 24
Overall	M = 21	M = 25

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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Chapter 11, Problem 9E

Chapter 11, Problem 11E

Chapter 11 Solutions

Research Methods for the Behavioral Sciences (MindTap Course List)

Ch. 11.1 - Define a factorial research design, including the...Ch. 11.2 - Define a main effect for one factor and an...Ch. 11.2 - Explain how the existence of an interaction can...Ch. 11.2 - Describe and explain the independent relationship...Ch. 11.3 - Explain how a factorial study can combine...Ch. 11.3 - Identify the statistical analyses that are...Ch. 11.4 - Describe three specific applications of the...Ch. 11 - In addition to the key words, you should also be...Ch. 11 - In a classic study, Shrauger (1972) examined the...Ch. 11 - Suppose a researcher conducts a two-factor study...

Ch. 11 - The following matrix represents the results (the...Ch. 11 - The following data show the pattern of results...Ch. 11 - Explain why the main effects in a factorial study...Ch. 11 - Explain what is meant by the concept that main...Ch. 11 - In Figure 11.5, we show three combinations of main...Ch. 11 - For a two-factor research study with two levels...Ch. 11 - A researcher would like to use a factorial study...Ch. 11 - A two-factor analysis of variance is used to...Ch. 11 - A researcher has demonstrated that a new...

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Introduction to experimental design and analysis of variance (ANOVA); Author: Dr. Bharatendra Rai;https://www.youtube.com/watch?v=vSFo1MwLoxU;License: Standard YouTube License, CC-BY

Solution Summary: The author explains that there are three F ratios in a factorial design, which involves experimenting with different factors.

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