Research Methods for Behavioral Sciences - With MindTap
6th Edition
ISBN: 9781337754989
Author: GRAVETTER
Publisher: CENGAGE L
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Textbook Question
Chapter 7.1, Problem 3LO
Describe the third-variable problem and the directionality problem, identify these problems when they appear in a research study, and explain why they must be eliminated before an experiment can demonstrate a cause-and-effect relationship.
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Chapter 7 Solutions
Research Methods for Behavioral Sciences - With MindTap
Ch. 7.1 - Describe the general purpose of an experimental...Ch. 7.1 - Define independent, dependent, and extraneous...Ch. 7.1 - Describe the third-variable problem and the...Ch. 7.2 - Explain why manipulation of an independent...Ch. 7.2 - Explain why control of extraneous variables is a...Ch. 7.2 - Explain how an extraneous variable can become a...Ch. 7.3 - Describe the three primary techniques for...Ch. 7.4 - Describe the purpose for control conditions in...Ch. 7.4 - Explain when a manipulation check is needed,...Ch. 7.4 - Define field studies and simulation, explain why...
Ch. 7 - In addition to the key words, you should also be...Ch. 7 - Dr. Jones conducted a study examining the...Ch. 7 - In an experiment examining human memory, two...Ch. 7 - It has been demonstrated that students with high...Ch. 7 - A researcher would like to compare two methods for...Ch. 7 - Define extraneous variable and explain how...Ch. 7 - Identify the two characteristics needed for a...Ch. 7 - Identify the two active methods of preventing...Ch. 7 - Explain how the process of randomly assigning...Ch. 7 - Can a research study be an experiment without a...Ch. 7 - What is the general purpose of a manipulation...Ch. 7 - What is the general purpose for using a simulation...
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- If the omitted variable is negatively correlated with the treatment and has a positive impact on the outcome, the true causal effect is bigger than the estimated effect. Blank 1: enter "True" or "False" Blank 2: explain briefly (1-3 lines).arrow_forwardIf changing variable A causes variation in variable B, then variable A is identified or described by researchers as what variable? More specifically, is variable A associated with the cause or the effect, the independent or the dependent variable? A. Dependent variable B. Independent variable C. Co-dependent variable D. Methodological variablearrow_forwardCan you Identify the explanatory variable and the response for this relationship, if possible?arrow_forward
- A survey of high school students was done to examine whether students had ever driven a car after consuming a substantial amount of alcohol (1=yes, 0=no). Data was collected on their sex (male/female), race (White/non-White), and grade level (9,10,11,12). Researchers realized that the impact of race on consuming alcohol before driving might vary by grade level and decided to fit the following model. Variable Coding = 1 if Intercept Sex () Female Race () Black Grade level ( 9th grade 10th grade 11th grade [Reference = 12th grade] Attached is the logistic model 1. Compute the OR of drinking before driving for students who self-reported as Black versus non-Black in the 9th grade, adjusting for gender. 2. Compute the OR of drinking before driving for students who self-reported as Black versus non-Black in the 12th grade, adjusting for gender. 3. Compute the OR of drinking before driving for someone in the 9th grade versus 12th grade for a student who…arrow_forwardOmitting a variable from our model that has a causal effect on our dependent variable always leads to omitted variable bias. a. False b. Truearrow_forwardRead through this scenario and look at the data that was collected. State the null and all possible research hypotheses. Review the results below (I used SPSS) and answer the questions that follow. Scenario: A researcher wants to see if gender and / or income affects the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affects the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables…arrow_forward
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