MT355 Unit 6 Published Study Seminar Reflection Example

The Chart Started at Twenty Percent: An MT355 Unit 6 Seminar Reflection on a Study I Almost Used

[Student Name]

Purdue University Global

MT355: Marketing Research and Analytics

Unit 6 Seminar Reflection

[Instructor Name]

[Date]

The seminar and the app report are composite; the sources cited are real.

The Study

The facilitator chose a report from a fitness app, which said that 62 percent of adults prefer evening group classes. It was based on 2,400 app users who answered an in-app prompt during one week in January. The report included a bar chart comparing evening preference with morning preference, 62 percent against 24 percent.

My Plan

After the pilot in Unit 5, our survey was running long, and I was looking for items to cut. The evenings grid was a candidate. If a large published study already showed that most adults prefer evenings, I thought, we could cite it and drop the grid, saving a minute of the respondents' time. I came to the session planning to do exactly that, and I said so when the facilitator asked how we might use the study.

The Dissection

The class took the study apart in three steps. First, who answered: app users, who are already exercising, answering during a week in January when many people make fitness resolutions. Adults who cannot swim, our target, may have very different schedules and constraints. Second, what came before the question: the timing item followed a block of questions about work stress, which might have primed respondents to think about their working day and favor evenings. Third, the chart: its vertical axis began at 20 percent, not zero, which made the gap between 62 and 24 look roughly four times larger than it is. Pandey et al. (2015) found in experiments that truncated axes lead viewers to exaggerate the size of differences, even when the numbers are labeled.

The study was not wrong about evenings; it was about different people, asked in a different context and drawn to look bigger than it was.

The Challenge

A classmate who works in health care argued that we were being too harsh. Even a flawed study, she said, can suggest a hypothesis worth testing. She was right about that. The report gives a reason to expect evenings to matter. I agreed with her partly: the study is useful as a hypothesis, but not as a substitute for asking our own population. Malhotra (2019) draws the same line between secondary data that can inform a research design and secondary data that can answer the research question.

Why I Was Tempted

I should be honest about why I wanted to use the study. The pilot had shown the survey running five minutes over its promised length, and the owner had asked me to shorten it before December. A published figure from a large sample offered a quick fix: one citation in place of a grid. I had not read the report's methods section before the seminar, only its summary and chart. In other words, I had done exactly what the class later criticized, trusting a source because it was convenient and looked professional.

The Decision

The evenings grid stays in the survey. It is the only way to learn which evenings our target adults could attend, and that answer determines which lanes we would schedule. To save time, I cut three items on past swimming experience instead, as the Unit 5 memo describes. I also noticed that our own inquiry log, in which 118 of 311 adult inquiries asked about evenings, is better evidence than the app study for our purposes, because it comes from people who contacted us.

What the Class Did Well

The dissection worked because the class asked the same three questions of the study that we had been taught to ask of our own surveys. Tourangeau et al. (2000) describe how earlier questions can shape later answers, and the work-stress block in the app survey was a clear example: someone who has just answered five questions about a draining workday may well imagine exercise after work rather than before it. I had read that idea in the textbook but had never applied it to a published report. The facilitator's choice of a study that looked authoritative, with a large sample and a professional chart, made the lesson stick. A sloppy study would have been easy to dismiss; this one had to be taken apart.

What I Learned

I was tempted to use the study because it said what I expected and saved me work. That is exactly when a source needs the most scrutiny. Next time I find a figure that conveniently answers my question, I will ask the same three questions the class asked: who answered, what came before, and how was it shown.

References

Malhotra, N. K. (2019). Marketing research: An applied orientation (7th ed.). Pearson.

Pandey, A. V., Rall, K., Satterthwaite, M. L., Nov, O., & Bertini, E. (2015). How deceptive are deceptive visualizations? An empirical analysis of common distortion techniques. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 1469-1478. https://doi.org/10.1145/2702123.2702608

Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The psychology of survey response. Cambridge University Press.