Ranking Algorithms. How to determine ranking out of complex data types. Ranking Topics in a Presentation. Ranking QBs in the NFL: Passer Rating. This formula is meant to measure a quarterback’s passing performance with a single numeric value. The passer rating scale is from 0 to 158.3
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
How to determine ranking out of complex data types
Scenario: Below are last games statistics. Which quarterback should the coach start next game?
Philip Rivers (current starter): PR = 108.7
Joseph Gast (backup): PR = 158.3
The goal: Since birth records are public, new parents are bombarded with marketing and advertising offers. Target’s goal was to identify parents before the baby was born.
More specifically, target wanted to be able to identify pregnant women in the second trimester and send them coupons for diapers, car seats, etc.
The outcome: Target was successful! Women thought it was creepy. The PR following effected Target negatively.
The solution: Continue to “target” (haha) pregnant women with relevant ads, however include purposefully non-relevant ads so they do not notice.
Pole found interesting changes in buyer behavior as their due date approaches, such as:
“Just wait. We’ll be sending you coupons for things you want before you even know you want them.” –Andrew Pole
Uses multiple variables to predict a linear relationship.
One dependent variable; k explanatory variables.
β = slope terms
Multiple Coefficient of Determination = R2
R2 always increases the more you add explanatory variables, however this does not mean the model is better.
= Adjusted R2; weighs errors more heavily by penalizing the model for adding bad explanatory variables.
of categorical variables. And how
they relate to other variables.
data into categories and
comparing the sum of squares
mean for each category to the
sum of squares total.
used as a weight so that larger samples have a greater effect.