Exam 1, Pt 2
2025-01-26
Quantitative
#Part A The mean tells at that the average amount of steps taken per day is 10749.34. The median tells us that the 50% value where half the data spread is above and below is 10919.5. The standard deviation tells us about the spread of the data and that it ranges between ~6000 to ~1500 steps a day indicating an irregular step count on a day-to-day basis.
##
## 114 1427 1792 4219 4291 4469 4632 4679 4888 4906 5183 5241 5643
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 6041 6413 6444 6826 7002 7258 7332 7345 7609 7760 7816 8026 8273
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 8318 8502 8806 8843 9125 9141 9184 9494 9809 9813 9892 10001 10485
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 10521 10626 10701 10706 10781 11058 11152 11286 11362 11443 11512 11520 11619
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 11737 12011 12104 12171 12367 12675 12760 12889 12902 13196 13414 13624 13631
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 13773 13799 13874 13904 14097 14212 14295 14702 15383 15400 15600 15731 16156
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 16220 16700 16982 17209 17299 17942 18136 18792 18804 20122
## 1 1 1 1 1 1 1 1 1 1## [1] 10749.34## [1] 10919.5## [1] 4304.674## [1] 2.497132#Part B The Q3 value of the data set tells us that 75% of the data fall below 13780 steps a day and that 25% fall above it. This shows us the “75th percentile” of steps/day.
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 114 7722 10920 10749 13780 20122#Part C From these box plots I can see which days have, on average, higher step counts, and which days have consistently higher step counts. For example, Thursday has the most steps on average, but the spread is larger, meaning there is less consistently as opposed to Wednesday which has less steps but is more consistent.
##
## 114 1427 1792 4219 4291 4469 4632 4679 4888 4906 5183 5241 5643
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 6041 6413 6444 6826 7002 7258 7332 7345 7609 7760 7816 8026 8273
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 8318 8502 8806 8843 9125 9141 9184 9494 9809 9813 9892 10001 10485
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 10521 10626 10701 10706 10781 11058 11152 11286 11362 11443 11512 11520 11619
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 11737 12011 12104 12171 12367 12675 12760 12889 12902 13196 13414 13624 13631
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 13773 13799 13874 13904 14097 14212 14295 14702 15383 15400 15600 15731 16156
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 16220 16700 16982 17209 17299 17942 18136 18792 18804 20122
## 1 1 1 1 1 1 1 1 1 1
#Part D January and February had similar step counts, but while February had a higher median, there were days with even less steps than January. January was consistently higher, with higher minimums, but the median was slightly lower. In March, the miles tailed off, clearly the New Year’s Resolution didn’t quite make it so far.
#Part E The data is skewed left, showing that the most common number of floors climbed is ~65. Then it tails off as the number of floors climbed decreases except for, it seems one day, where between 120 and 140 floors were climbed, maybe a hike.
####Qualitative #Part A January is the largest section for both data representations, because it has the largest data selection with 31 days and February has the smallest because it has only 28 days.
##
## Feb Jan March
## 28 31 29
#Part B This shows the amount of each day in each month, side by side. This can provide more insight into why some months may have more steps, because some days are more conducive to getting more steps, such as a day with a scheduled run or walk, or a day that walking is part of the routine commute.
##
## Feb Jan March
## F 4 5 4
## M 4 4 5
## R 4 4 4
## Sat 4 5 4
## Sun 4 5 4
## T 4 4 4
## W 4 4 4
#Part C This clearly shows how many of each day are in each month, which, as said in Part B, can give insight into why some months may have higher step-count average, because they have more days with higher step averages where steps, miles, sleep, etc. is a larger part of that specific daily routine.
##
## Feb Jan March
## F 4 5 4
## M 4 4 5
## R 4 4 4
## Sat 4 5 4
## Sun 4 5 4
## T 4 4 4
## W 4 4 4