Exam 14: Two Too Many Factors: Factorial Analysis of Variancea Brief Introduction
Exam 1: Statistics or Sadistics Its up to You50 Questions
Exam 2: Means to an End: Computing and Understanding Averages79 Questions
Exam 3: Vive La Différence: Understanding Variability80 Questions
Exam 4: A Picture Really Is Worth a Thousand Words41 Questions
Exam 5: Ice Cream and Crime: Computing Correlation Coefficients77 Questions
Exam 6: Just the Truth: An Introduction to Understanding Reliability and Validity77 Questions
Exam 7: Hypotheticals and You: Testing Your Questions73 Questions
Exam 8: Are Your Curves Normal Probability and Why It Counts76 Questions
Exam 9: Significantly Significant: What It Means for You and Me78 Questions
Exam 10: Only the Lonely: The One Sample Z-Test79 Questions
Exam 11: Tea for Two: Tests Between the Means of Different Groups69 Questions
Exam 12: Tea for Two Again: Tests Between the Means of Related Groups81 Questions
Exam 13: Two Groups Too Many Try Analysis of Variance77 Questions
Exam 14: Two Too Many Factors: Factorial Analysis of Variancea Brief Introduction77 Questions
Exam 15: Cousins or Just Good Friends Testing Relationships Using Correlation Coefficient75 Questions
Exam 16: Predicting Wholl Win the Super Bowl: Using Linear Regression79 Questions
Exam 17: What to Do When Youre Not Normal: CHI-Square and Some Other Nonparametric Tests75 Questions
Exam 18: Some Other Important Statistical Procedures You Should Know About47 Questions
Exam 19: Data Mining: An Introduction to Getting the Most Out of Your Big Data50 Questions
Exam 20: A Statistical Software Sampler9 Questions
Exam 21: The Ten or More Best and Most Fun Internet Sites for Statistics Stuff9 Questions
Exam 22: The Ten Commandments of Data Collection10 Questions
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Like the scatter plot in a correlation, one of the easiest ways to see the magnitude of an interaction (or the absence of one) in a factorial ANOVA is to plot the means.
(True/False)
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In a factorial ANOVA, one of the null hypotheses might look like this:
A)
B)
C)
D)
(Short Answer)
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If your main effects are significant, your interaction effects will also be significant in all cases.
(True/False)
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In the main effect F₍₁,₁₂₎ = 5.25, p < .05, what does the symbol p stand for?
(Multiple Choice)
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If your analysis notes that males in a weight loss study differ from females in the weight loss study in the amount of weight lost based on the type of weight loss program used, what type of effect is this called?
(Multiple Choice)
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An interaction effect is a phenomenon where the effect of one independent variable on the dependent variable differs based on the level of a second independent variable.
(True/False)
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An analysis that examines more than one dependent variable or outcome is known as _______ ANOVA.
(Multiple Choice)
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Which of the following would be an example of a design that examines the effects gender and school type (i.e., elementary, middle, or high school) on a scale of student attitudes toward learning?
(Multiple Choice)
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In a factorial ANOVA, one of the null hypotheses for a main effect might look like this:
A)
B)
C)
D)
(Short Answer)
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How many research hypotheses are used in a 2 × 2 factorial ANOVA?
(Multiple Choice)
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If you wanted to examine whether television viewing through social learning differs based on students' grade in school (i.e., first, second, third, etc.), what is the independent variable of interest?
(Multiple Choice)
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What are the three research hypotheses used in a 2 × 2 factorial analysis?
(Essay)
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When analysis of data reveals a difference between levels of a factor, what is this called?
(Multiple Choice)
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