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The data we will analyze this week is a survey of sport fans’ experiences during COVID-19. My lab was interested in how sport fans were doing during COVID and whether being fans had an effect on their well-being.
1. Download the files below:
Covid.Dataset.xlsx Download Covid.Dataset.xlsx
Covid.Dataset_Students.pptx
You will use the Excel file for your analysis. The PowerPoint file provides information about the dataset for your reference.
2. Watch this video demonstrating how to run correlation analysis using Excel’s Data
Analysis ToolPak:
https://youtu.be/T9KM2wJjnmMLinks to an external site.
3. Following the instructions shown in the video, run a correlation analysis by selecting at least four variables: choose at least two variables that you think will be highly correlated
with each other and at least two variables that you think will be weakly correlated with
each other. The variables you select should include new variables that were not used in
the demonstration video.
4. Answer the four questions below in a .docx document. This will be your PR4.
(1) What
were your variables? Copy and paste your correlation table to your document.
(2) Which correlation was the strongest and weakest among the variables?
(3) Does this make sense to you or not? Please explain.
(4) Are there any interesting patterns between
the variables? Please elaborate.
(5) Conduct a Google search and find a journal article(s) that reported similar or different results. Explain how it is similar or different.
[Tips:
Correlations range from -1 to 1. 0 is the weakest correlation, 1 is a perfect positive
correlation, and -1 is a perfect negative correlation.
To simplify it: it gives us an estimate
on how one unit change in one variable (SD in r) is associated with r unit change in
another variable (SD in r) .
So, the larger the (absolute) coefficient value, the larger the
association.]
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