this is for holding javascript data
Chris Spencer edited Question 9.tex
about 10 years ago
Commit id: 10aa5a62cf84aca2f298abc51e91928b44b71685
deletions | additions
diff --git a/Question 9.tex b/Question 9.tex
index d773f41..20e866e 100644
--- a/Question 9.tex
+++ b/Question 9.tex
...
\subsection{Question
9} 10}
Here I graphed OPS vs runs, where OPS is on-base percenatage + slugging percenatage. Sluggin percentage is total bases/at-bats. It can be seen from the graph below that the relationship has a strong linear relationship. This graph give an $r^2=0.93$ and a $r=0/96$. This means this model is incredibly good at explaining variation and a strong linear relationship. The slope is$1.93*10^3$, so this means that every 1 increase in OPS, on average your runs will go up by the value of the slope. Considering how strong a linear relationship this is, this will predict runs very well. This makes sense in context of number 6 in that I thought that the more homeruns you hit the more runs you get. OPS has slugging percentage in it which is determined by at bats in the denominator. So if your at bats is less than you slugging percentage goes up. Hitting homeruns means your at bat significantly less so this result doesnt suprise me.