Question

Suppose that a researcher wants to study the effects of chocolate consumption on attitudes about the nutritional effects of candy. The researcher believes that people will have more favorable attitudes about the nutritional benefits of candy after consuming a chocolate bar. The researcher selects two groups of subjects (Group C and Group NC), each consisting of 20 students. The subjects in Group C are recruited from students in a History of Chocolate course. The subjects in Group NC are recruited from an Introduction to Bowling course. The subjects in Group C will eat a chocolate bar and the students in Group NC will eat no chocolate. Then all subjects will be given a survey that measures attitudes about the Nutritional Benefits of Candy (the NBC survey), which yields a score between 0-100. A high score on the survey indicates that the subject believes that candy has large nutritional benefits. The researcher plans on (1) conducting the research in his lab, (2) allowing subjects in Group C to choose the brand of chocolate bar they will eat from two options, and (3) testing the null hypothesis at the .01 level of significance, but the researcher has flexibility in these aspects of the research design. However, the researcher does not have access to any additional subjects.

1. What are the independent variable and the dependent variable in this study?

2. The researcher wants to know if chocolate consumption affects the subjects’ attitudes. What is it about the way in which Groups C and NC were formed that might prevent the researcher from drawing strong conclusions about the effects of chocolate consumption?

3. How would you categorize this research design? In other words, what broad category of research design would this fall under?

4. Is the course from which subjects were chosen a confound? Why or why not?

5. Assuming that different subjects in Group C choose different types of chocolate to eat, is the type of chocolate bar chosen by the subjects in Group C a confound? Why or why not?

6. What type of inferential statistical test should the researcher use to analyze his data? Be specific enough so that a graduate research assistant assigned to run the statistical test would know what type of statistical test to run on a computer.

7. How would you state the null hypothesis for this statistical test?

8. How would you describe a Type II error in the context of this research? (Refer to chocolate consumption and attitudes about nutritional benefits of candy.)

9. How can the researcher decrease the probability of a Type II error in his research? (Remember that the researcher in this case cannot increase the number of subjects.)

Answer 1

Answer:

1) The independent variable is chocolate consumption. The dependent variable is attitudes towards nutritional effects of candy.
2) The researcher has not randomly assigned participants to the Group C and Group NC conditions. This means that the researcher cannot accurately draw a cause and effect relationship between the variables.
3) This is a quasi experimental design.
4) The course from which subjects were chosen is a confound. This is because the researcher put subjects from one course into one group and subjects from another course into another group. There maybe several pre-existing differences between the groups already and these may have an impact on the dependent variable.

5. This will be considered a confound. There should be minimal differences in the treatment of each participant so that these variables do not affect the independent-dependent variable relationship. Therefore, all participants in the group should be given the same chocolate.

6. An independent samples t-test should be used.

7. Null hypothesis: There is no significant difference between Group C and Group NC in their attitudes about the nutritional effects of candy.

Alternative hypothesis: There is a significant difference between Group C and Group NC in their attitudes about the nutritional effects of candy.

8. A Type II error would be the results of the study finding no significant differences between groups when in reality, there is a significant difference between the groups.

9. The researcher can increase the significance level so as to reduce the chances of making a Type II error. Here, the researcher has chosen the 0.01 level of significance, which is quite stringent. The researcher can instead choose the 0.05 level of significance.

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