Week 8: Correlation Analysis
Hello everyone! Welcome back to my blog!
I now have 41 responses, and I also have 2 people who have given me their consent forms but have not yet taken my survey. Additionally, I’ve reached my goal of 30 responses from school students! Now, I just have to wait until I reach my goal of 30 responses from college students.
Since I’ve gathered most of the student responses, I decided to start analyzing the data. As I mentioned earlier, there are so many things I can analyze using my data, but in today’s post, I’d like to focus on how I’m analyzing the data specifically to answer my research question.
How I’m Analyzing My Data
My goal is to examine the relationship between intrinsic motivation and performance anxiety as well as extrinsic motivation and performance anxiety. In my survey, I included:
- 3 questions measuring intrinsic motivation
- 3 questions measuring extrinsic motivation
- 5 questions measuring performance anxiety
Most responses are measured on a Likert scale (1-5), where 5 indicates higher levels of motivation or performance anxiety. Since performance anxiety had 2 more questions than the motivation measures, I decided to calculate the average score for each category and participant, so all the final numbers stayed between 1 and 5, which allowed for accurate correlations.
The 1 survey question that isn’t measured on a Likert scale is the one that asked participants to check off any physical symptoms of anxiety they experience. Originally, I was thinking about converting this question into a numerical value by counting the number of symptoms selected. However, I realized that having more symptoms doesn’t necessarily mean someone has higher levels of performance anxiety—factors like the intensity of the symptoms also play a role. So, I chose not to include this question in my calculations. However, I still want to analyze which symptoms were most commonly reported because I think that could also help us find the best coping strategies.
Running Correlation Analyses
To analyze my data, I used Google Sheets to calculate the Pearson correlation coefficient (r),which helps determine how closely two sets of data are related. Here’s how I did it:
- To find the correlation between intrinsic motivation and performance anxiety, I used the formula: =CORREL(Q2:Q42, S2:S42)
- To find the correlation between extrinsic motivation and performance anxiety, I used the formula: =CORREL(R2:R42, S2:S42)
Q represents the column with the intrinsic motivation scores, R represents the column with the extrinsic motivation scores, and S represents the column with the performance anxiety scores. The numbers represent the range of participant responses. For example, Q2:Q42 refers to the intrinsic motivation scores for participants 2 through 42.
Next, I calculated the t-value and p-value to determine whether my correlations were statistically significant. For a result to be statistically significant, the p-value must be below 0.05.
So far, I’ve found interesting results! However, I want to wait until I’ve collected all my data before sharing my findings. Thank you so much for reading, and stay tuned for more updates!
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