Research Methods for the Behavioral Sciences
5th Edition
ISBN: 9780357231913
Author: Frederick J Gravetter; Lori-Ann B. Forzano
Publisher: Cengage Limited
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Chapter 9, Problem 2E
Describe the characteristics of a within-subjects experimental research design.
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Chapter 9 Solutions
Research Methods for the Behavioral Sciences
Ch. 9.1 - Describe the general characteristics of a...Ch. 9.1 - Describe how time-related factors such as history,...Ch. 9.2 - For a within-subjects experiment, explain how the...Ch. 9.2 - Define counterbalancing and explain how it is used...Ch. 9.2 - Describe the limitations of counterbalancing and...Ch. 9.3 - Explain the general advantages and disadvantages...Ch. 9.3 - Define a matched-subject design and explain how it...Ch. 9.4 - Describe the different ways that within-subjects...Ch. 9 - In addition to the key words, you should also be...Ch. 9 - Describe the characteristics of a within-subjects...
Ch. 9 - Briefly explain how an order effect such as...Ch. 9 - Under what circumstances is it advisable to switch...Ch. 9 - Describe the process of counterbalancing and the...Ch. 9 - Describe the circumstances in which...Ch. 9 - What is the advantage of removing the variability...Ch. 9 - Explain how a within-subjects design avoids the...Ch. 9 - A researcher has a sample of 30 rats that are all...Ch. 9 - Explain how a matched-subjects design attempts to...Ch. 9 - Describe the disadvantages of a multiple-treatment...Ch. 9 - researcher has a sample of 30 rats that are all...Ch. 9 - In a Latin square, each treatment condition occurs...
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- A researcher is investigating the effectiveness of two weight loss treatments. The number of patients attending Treatment A and Treatment B are 30 and 32 respectively. The patients’ weight losses (in Kg) after a two-month treatment period are recorded and shown in Table 1: What type of research design you think this research should be classified? Explain your answer. Based on the research objective of the study, identify the: Independent and dependent variables of this research. Scale of measurement of each of the independent and dependent variables. For EACH of the treatment, determine/construct the following measures and histograms of weight losses using SPSS or any suitable statistical analysis tool: Mean Median Range Histogram d. Based on the histograms of weight losses produced in (c), briefly describe: The shape of distribution of weight losses for EACH treatment. How does the distribution of Treatment A differ from Treatment B e.…arrow_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_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 affect 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 - affect 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
- Does the presence of a significant interaction change the interpretation of significant main effects? Provide one example including a minimum of two independent variables.arrow_forwardWhy is it a good idea to center your variables when conducting a moderation analysis? A. Because it reduces multicollinearity between main effects and the interaction effect B. It makes the data normally distributed. C. It ensures the relationship between the predictor and outcome is linear. D. It aids the interpretation of the indirect effect.arrow_forwardSuppose a researcher wants to see if the proportion of college educated adults is higher in New York compared to Florida. The researcher randomly samples 500 adults in New York and found that 196 had a college education, while a random sample of 600 adults in Florida found that 227 had a college education.At the 0.05 level of significance, does the data provide evidence to suggest the proportion of college educated adults is higher in New York than Florida? Step 1: Define the parameter & setup the testStep 2: State the Level of SignificanceStep 3: Find the value of the Test StatisticsStep 4: Find P-Value OR Find Critical ValueStep 5: State Conclusion and whyarrow_forward
- What are the requirements for an experiment to be able to show that changes in one variable cause changes in another?arrow_forwardSeedlings of an annual plant were split into two equal treatment groups; in one group, extra fertilizer was provided, and in the other group (the control group), no additional fertilizer was added. The numbers of seeds and the average weight of the seeds from each individual plant were monitored, and these data were plotted (each point represents an individual plant). Which statement best describes the results of this study? Control With fertilizer 450 400 400 350 350 300 300 250 250 200 200 130 130 100 100 50 50 10 20 30 40 50 70 10 20 30 40 50 Number of seeds Number of seeds O A. Trade-offs between seed size and seed number exist in both the control and the fertilizer groups, and these trade-offs are of roughly equal magnitude. B. Trade-offs between seed size and seed number exist in both the control and the fertilizer groups, but these trade-offs are much larger in the fertilizer group. C.A trade-off between seed size and seed number exists in the control group but not in the…arrow_forwardDiscuss the three types of longitudinal research methods. When is each method an appropriate choice of data collection? Discuss the difficulties of each method.arrow_forward
- A study was undertaken in a hospital to compare the performance of a new surveillance method to the standard method in the ability to detect patients who develop an infection after a caesarean section. Individual record data from this study is provided in the file called surveillence.dta. The dataset contains the following variables: ID: Patient identification number new: Assessment of cases by the new surveillance method (1=Positive, 2=Negative) standard: Assessment of cases by the standard method (1=Positive, 2=Negative) ID new standard 1 negative negative 2 negative negative 3 negative negative 4 negative negative 5 negative negative 6 negative negative 7 negative negative 8 negative negative 9 negative negative 10 negative negative 11 negative negative 12 negative negative 13 negative negative 14 negative negative 15 negative negative 16 negative…arrow_forwardIf there is a significant interaction for a CRD with a two-way treatment structure, then one should assess whether the main effects are significant. True or falsearrow_forwardAs a good experimenter, you have built a predictive model of the experimental data. The differences between the actual response data and the model data are termed: A. Confounded data B. Nested experiments C. Residuals D. Efficiency of estimatorsarrow_forward
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