ASAP - Mile 23

[Image/Calculations done using Desmos.com]

Geeking Out: Just for fun, I 'ran' a linear regression model for my shoe charity project with several computational violations noted below. X is the number days since 2016 when the shoe deliveries were made (donations were made on the 23rd, 37th, and 54th day of 2017). Y is the cumulative number of pairs of shoes donated on those days (we started with 3 pairs in Corral #1, added 6 pairs in Corral #2 for a total of 9, and just delivered 3 more pairs in Corral #3 to bring the total up to 12). The slope is about 0.29, which means that the project donates, on average, just over a quarter of a pair of shoes each day in 2017. That's not bad, it's more than half of a shoe a day. The y-intercept of about -2.88 is not meaningful in this case. It translates to the project donated a negative 2.88 pairs of shoes on midnight of New Years Eve.* The model predicts that by the end of the year (365 days into 2017), 101.6 pairs of shoes will be donated.** There is a strong positive correlation of 0.96 between days since 2017 and the number of pairs donated. Lastly, about 92% of the variation in the number of pairs donated is accounted for by the number of days since 2016. With only three data points, however, it may not be appropriate to use a linear model, rendering this analysis meaningless. But thanks for reading.

*I promise that I did not remove 2.88 pairs of shoes from those in need on New Years Eve.
**Extrapolation is committed. Using the limited existing data to project a value far outside the range of our x-values leads to unrealistic and inaccurate predictions. It's impossible to donate 101.6 pairs of shoes, let alone by the end of the year. The number of pairs of shoes should be an integer value. An ambitious goal of 101 or 102 pairs is also extremely unlikely. The residual (actual value - predicted value) will likely be negative on New Years Eve 2017.

https://www.desmos.com/calculator/qw4m3fzi5w