STAT151 Lecture Notes - Lecture 7: Apolipoprotein A1, Sumo Protein, Cierva C.40

• School: University of Alberta
• Department: Statistics
• Course: STAT151
• Professor: Rosana Fok

Document Summary

Stat 151: lecture 7 - correlations part 2 & linear regressions. Correlation tables - it is common to compute the correlations between every pair of variables and arrange them in a table. Done by statisticians in order to make better predictions. A linear graph means they have proportional data. When a graph is bent, a statistician will often re-express the variables to make it straight. Just because we see in a graph that as the x-variable increases, the y-variable also increases, his does not mean that x causes y. Example: if we graph the number of firefighters as our x-variable, and the damage done to a forest as our y-variable, we will see that both will increase. This does not mean that the damage done in a fire was caused by the firefighters. This could mean that there are lurking variables on the data.