Correlation and Causation. Part II – Correlation Coefficient. This video is designed to accompany pages 19-24 in Making Sense of Uncertainty Activities for Teaching Statistical Reasoning Van- Griner Publishing Company. Defining a Need.
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Correlation and Causation
Part II – Correlation Coefficient
This video is designed to accompany
Making Sense of Uncertainty
Activities for Teaching Statistical Reasoning
Van-Griner Publishing Company
Defining a Need
The Correlation Coefficient is simply a numerical way of summarizing the relationship you’d see between two variables that you could represent with a scatterplot.
How strong is it?
Formula for “r”
The Correlation Coefficient is “r” measures the strength of the linear relationship between two variables “x” and “y”.
Before we compute it …
It is only appropriate to compute r if the scatterplot of y versus x exhibits a linear trend
r will always be between -1 and 1.
r will be negative if the points in the scatterplot have a downward trend from left to right
r will be positive if the points in the scatterplot have an upward trend from left to right
The closer r is to 1 in absolute value the tighter the cluster of points about the linear trend and the stronger the association between x and y
If r is close to 0 then the association is weak.
Moderate, positive correlation?
r = -0.93
r = 0.75
Time Spent Studying
Life Expectancy at Birth
Final Exam Score
Not appropriate to use r since plot is curved
r = 0.02
GNP per capita
The correlation coefficient is the most common numerical measure of the strength of a straight line relationship between two variables that can represented by a scatterplot.