# Chapter 7 - linear 4 Existence of strong correlation does...

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Chapter 7 – Scatterplot, Association and Correlation ActivStats: 7-1 to 7-4 Read: Chapter 7 A scatterplot displays a relationship between two quantitative variables. In a scatterplot a variable assigned to x-axis is called explanatory (or predictor) , and a variable assigned to y- axis a response variable. Often a response variable is a variable that we want to predict.

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Things to look at: Direction (negative or positive) Strength (no, moderate, strong) Form (linear or not) Outliers Correlation Coefficient r is a measure of the strength of the linear association between two quantitative variables.
Properties 1. The sign gives direction 2. r is always between –1 and 1 3. r= 0 indicates lack of linear association (but could be strong non-
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Unformatted text preview: linear) 4. Existence of strong correlation does not mean that the association is causal , that is change of one variable is caused by the change of the other (it may be third factor that cause s both variables change in the same direction) Computation y x s s n y y x x r ) 1 ( ) )( (---= ∑ Where x s = standard deviation of sample x, and s y = standard deviation of sample y Example: x y (x - x ) (y - y ) Product 6 5-8-2 16 10 3-4-4 16 14 7 19 8 5 1 5 21 12 7 5 35 Sum 70 35 72 Mean 14 7 s 6.20 3.39 2 4 6 8 10 12 14 5 10 15 20 25 856 . 39 . 3 20 . 6 ) 1 5 ( 72 = × ×-= r...
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Chapter 7 - linear 4 Existence of strong correlation does...

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