Question

The report "Undergraduate Students and Credit Cards in 2004: An Analysis of Usage Rates and Trends" (Nellie Mae, May 2005 ) estimated that \(21 \%\) of undergraduates with credit cards pay them off each month and that the average outstanding balance on undergraduates' credit cards is \(\$ 2169 .\) These estimates were based on an online survey that was sent to 1260 students. Responses were received from 132 of these students. Is it reasonable to generalize the reported estimates to the population of all undergraduate students? Address at least two possible sources of bias in your answer.

Short answer

No, it is not reasonable to generalize the reported estimates to the population of all undergraduate students because of potential sources of bias such as non-response bias and selection bias.

Step-by-step solution

Understanding the Exercise

In the exercise, estimates about credit card usage and outstanding balance for undergraduate students are made based on an online survey sent to 1260 students, and the responses were received from 132 of these students. The goal here is to ascertain whether this data could be generalized to all undergraduate students and identify potential sources of bias.

Generalizing Results

When looking to generalize results from a survey or experiment to a larger population, it is important that the sample being studied is representative of the overall population. In this case, the sample consisted of 132 students out of 1260 who were reached out to. However, the sample does not necessarily represent all undergraduate students because there was no information provided regarding the representativeness of the sample (e.g., are they from different colleges, different fields of study, different age groups etc.) Further, only 10.4% of students who were approached actually responded, which can introduce non-response bias.

Identifying Potential Sources of Bias

Two sources of bias that might affect these results are: (1) Non-response bias: As only 10.4% of approached students responded, this could introduce bias as the students who didn't respond might have different credit card usage patterns. (2) Selection bias: The students approached were reached online, which might exclude students who do not regularly check or use online platforms and could have different credit card usage habits. Also, if students from a single or limited number of institutions were surveyed, the sample might not represent the diverse situations of all undergraduate students nationwide.

Conclusion

Considering these potential sources of bias, it would not be reasonable to directly generalize the reported estimates to the population of all undergraduate students without further investigation or adjustment for these biases.