December Update: Preparing for Data Analysis

Happy holidays, everyone! Since I will be on campus until the last day of finals, December 20, I’ve been able to get a good chunk of work on my thesis done. We concluded data collection for the semester on December 11. After the final participant, I was able to start downloading and organizing all of my data to prepare for analyses. For the video study, we used 4 online Qualtrics questionnaires and 2 computer tasks. For the Qualtrics questionnaires, in order to get the data prepared for analyses, I had to download the data from Qualtrics, score each individual questionnaire, and combine each of the spreadsheets in SPSS.

This was the easy part. Next, I had to tackle the implicit computer task data, with a lot of help from my advisor. When you download the data from these tasks, it creates a huge spreadsheet (over 30,000 rows for one of them). This is because each trial for each participant creates its own row, and there were many trials for each participant. You then have to work to make sure all of the columns line up with each other. Then, you can start eliminating the columns you don’t need. Then, you need to eliminate the trials (rows) where the reaction times were way too long or way to short, that is, the outliers. All of this reduces the size of the spreadsheet a little. Next, you can create pivot tables. Pivot tables allow you to take that entire huge spreadsheet and reduce it down to 120 rows and 5-10 columns. Pivot tables include means or counts of variables for each participant. This is the data that is meaningful and can be used for analyses.

Now that all of this is complete, we can start analyzing the data. I’m very excited to see what we find!


  1. dkwolfe: Thank you for your encouragement! I agree, the data cleaning was very time consuming and required meticulous focus. I have finally analyzed the data, so it has been especially rewarding to see how a giant data set can go from thousands of numbers to significant findings.

    Kevin: Thank you for your kind words. Reflecting the entire process thus far of designing a project, analyzing the data, and finally writing up the findings, it has been incredibly satisfying to see the progress.

  2. Great job on finishing up your data collection and cleaning. While this is usually the “easy” part, it can certainly be the most grinding (and least fun). As someone who has worked with a lot of data, I know that it can be difficult to see the finial product in the midst of thousands of rows and columns. Be sure to keep pushing though. I hope it turns out well, and it sounds like you have made it to the other side.