Question

In this discussion board assignment, you will critically evaluate the following scenario using the four basic critical questions. Here is the scenario:

Researchers wanted to study the relationship between pizza consumption by college freshmen and academic achievement. The researchers selected a freshmen history class with 900 students. The class lasted for 16 weeks and had weekly quizzes.

The researchers used random sampling and got two equivalent groups of participants from the class. Each group had 35 students. One group was the pizza group and one was the non-pizza group. To prepare for the experiment, the researchers compared the average quiz results of both groups for the first three weeks of the course and found no statistically significant difference between quiz scores.

In weeks 4 - 12, the researchers provided pizza dinner for everyone in the pizza group but those in the non-pizza group were told not to eat pizza 48 hours before the weekly quizzes. After week 12, the researchers compared the average quiz scores in each group and found that the non-pizza group had a statistically higher average quiz score than the pizza group. The researchers concluded that pizza consumption hinders academic performance of college freshmen.

Here are the basic 4 critical questions:

The next step to critically evaluate correlational claims is asking our four basic CRITICAL QUESTIONS applied to correlation (p. 118):

What does the claim of correlation mean? Which two variables, changing events, factors, or things co-vary? Do they exhibit a positive or negative relation?

How good is the evidence? Are two relevant groups being compared? Is the difference between the groups large enough (i.e., outside the margin of error of both samples) so that it is unlikely that these differences are the result of chance sampling variation? Were the groups being compared appropriately selected?

What other information is relevant? What is the context? Have other researchers found similar correlations? Of similar strength? Did other researchers use different types of samples and groups?

Are relevant fallacies avoided? For example, consider the fallacies of No comparison, Biased Sampling, Small Sample, Unclear Target Population, and of Significance.

These fallacies are clearly described in our textbook. Since most have been already covered in the previous chapters of our textbook, corresponding online links, and in the Keynotes, we need only introduce the new fallacy of Significance. The error of reasoning here for this fallacy is to argue that the difference between two (sample) groups, in a strict statistical or scientific sense, is important—relying on the common usage of the word “significant.” In contrast, the “[d]ifferences are said to be ‘statistically significant’ when…we can theoretically be 95% confident that the differences are not due to chance” (according to what we learned about statistical reasoning in Chapter 3 of our textbook; p. 105, emphasis added). This, therefore, merely provides a probabilistic judgement about a result that is basically not significant or important in any ordinary sense. As Mark Battersby notes, “[a] ‘statistically significant difference’ between two groups means that it’s very likely that there’s a correlation; but this says nothing about the strength of the correlation or about whether the correlation is of any human, scientific, or personal significance” (pp. 114-115, emphasis added).

Answer 1

1. What does the claim of correlation mean?

Claim of correlation indicates the extent to which two variables fluctuate together. In our case calim of correlation indicates that how strongly we can predict the relationship between pizza consumption and academic performence.

a.Which two variables, changing events, factors , or things co-vary?

In this case Pizza consumption and academic performence are two variables. number of weeks are changing events.

b.Do they exhibit a positive or negative relaiton?

Yes, there is negative relation in between pizza consumption and academic performence. We found this after 12 weeks . We are failed to found this after 3rd week beacuse of restricted range.

2.How good the evidence?

Evidenve is good because it is showing significant difference in between two variables.

a.Are two relevant groups being compared?

Two relevant groups are compared for 12 weeks to get prediction

b.Is the difference between the groups large enough (i.e., outside the margin of error of both samples) so that it is unlikely that these differences are the result of chance sampling variation?

Difference is large enough because both samples have 35 participants and both are randomly selected.

3. What other information is relevant?

The information releavant ot this research 35 participant sample generalizing 900 students that persons who are highly consumes pizza scores less marks in academic performence

4.Are relevant fallacies avoided?

yes, relevant fallacies are avoided.

a. comparison: both samples are compred for 12 weeks to predict negative correlation

b.Biased sampling: there is no biased sampling because samples are selected randomly

c.Un clear target population : No, because there is clear population target that is 900 students.

d.Significance: yes, there is significance in research