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Correlation and CausationPowerPoint Presentation

Correlation and Causation

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Presentation Transcript

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

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.

Positive association.

How strong is it?

The Correlation Coefficient is “r” measures the strength of the linear relationship between two variables “x” and “y”.

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?

Got it!

Student Grades

LDL Levels

r = -0.93

r = 0.75

Time Spent Studying

Hours Exercised

Life Expectancy at Birth

Final Exam Score

Not appropriate to use r since plot is curved

r = 0.02

GNP per capita

Quiz Average

One-Sentence Reflection

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.

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