We Do Math in a Minute

1. We Do Math in a Minute Steve and Torsten

2. Introduction • In our experiment we had two version of a basic multiplication table. One was in order starting with 1x1, 1x2, 1x3 and so on. The other test was had randomized questions. We alternated which test was given, as well as which writing utensil (either pen or pencil) was used. Then, each subject had a minute to complete as many problems as they could. We were looking to see if gender, test type, and/or writing utensil had an impact on test performance.

3. Overall Quantitative Data The shape of the overall data is left skewed, with a median at 48.5 questions answered in a minute. The data is pretty spread out with an IQR of 33. We have an unusual peak 22.5-27.5 questions answered range. This could be explained by the different test types given.

4. Normality The data is fairly linear on the normal probability plot, and therefore it is fair to assume that the population of multiplication test answers is normal.

5. Gender The male graph is symmetrical and unimodal, while the female graph looks bimodal. The median of the male graph is 47 questions answered, while the females have a higher median of 54 questions answered. The females IQR is 37, and the males is 22, so the males had a much smaller spread of data than females did.

6. Test Type The shape of the organized test’s results looks symmetrical, while the randomized test’s results look right skewed. The organized test had a median of 62.5 questions answered (out of 75). The randomized test had a median of 29.5 questions answered (out of 60). The randomized test had an IQR of 16, which is only a little larger than the organized test’s IQR of 12.

7. Partner Steve’s test results were generally left skewed, while Torsten’s test results were very slightly right skewed. Steve’s median score was 48.5 questions answered, and Torsten’s median score was 50.5 questions answered. Steve had an IQR of 33, and Torsten had an IQR of 36. The skewedness may be explained by the difference in class taking the test. Steve administered to Mr. Wheeles’ and Mrs. McNelis’ classes, while Torsten only administered to Mrs. McNelis’ class.

8. Categorical Data

9. Marginal Distribution The percentage distributions for Gender are 58.33333% for females and 41.66667%. The percentage distribution for Test Type is 50% ordered and 50% random.

10. Conditional Distribution Within Females: 47.6% ordered, 52.4% random Within Males: 53.3% ordered, 46.7% random Within Ordered: 55.6% female, 44.4% male Within Random: 61.1% female, 38.9% male

11. Independence • The composition of the distribution graphs of gender and test type are nearly identical. We had different numbers of men and women take the test, which accounts for the difference in the numbers • We know that gender and test type are independent in this situation because we determined which test each person would take

12. Conclusion • Neither gender is necessarily better at multiplication tables than the other, but everyone is better at ordered tables than they are randomized tables. • The writing utensil used had no significant impact on test performance. • Also, as a fun fact. Through our observations of the test, we noticed a pattern. Men are far more likely to go in order of the problems, only skipping one if they don’t know it. Women skip around far more, oftentimes moving in patterns. Strangely, both methods achieved similar results.