I’d rather be knitting…
For discussion in my Statistics class, we were provided with the following set of questions. Since I was irritated that I had to work on this project rather than my Christmas knitting, I decided to combine the two:
Provide an example of how you could utilize correlation analysis for either a personal project or work related project.
1. What you would identify as the dependent variable (Y) and the independent variable (X)?
2. What you hypothesize might be the relationship between your X and Y variables?
3. How you would go about collecting your data?
4. What other variables (i.e., other Xs) that might impact your dependent variable?
5. What you think may be some of the benefits of correlation analysis vs. some of the deficiencies?
My correlation analysis concerns Christmas knitting. The dependent variable (Y) would be the number of knitted gifts that can be completed by Christmas. The independent variable (X) is the number of hours I devote to knitting. I would hypothesize that the relationship between my X and Y values will be positive; the more hours I spend knitting, the more projects I will complete. I would collect my data by charting the number of days remaining until Christmas. I would track how many hours I spent knitting, and how many projects I finished. Other variables that might impact my dependent variable would be the size of the project (hat versus sweater), thickness of the yarn (laceweight vs bulky), and the number of mistakes made that require ripping back. The benefit of correlation analysis is that it allows you to identify possible correlations between two variables. A major deficiency is that it only allows for the comparison of two variables, X and Y, and neglects other variables that might be significant factors.
And yes, in case you are wondering, I did post this to the class discussion forum. Homework complete, time to go knit.