Correlation and Causation
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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

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Correlation and causation

Correlation and Causation

Part II – Correlation Coefficient

Correlation and causation

This video is designed to accompany

pages 19-24


Making Sense of Uncertainty

Activities for Teaching Statistical Reasoning

Van-Griner Publishing Company

Correlation and causation

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.

Positive association.

How strong is it?

Correlation and causation

Formula for “r”

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

Correlation and causation

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.

Correlation and causation

Simple Scatterplot

Moderate, positive correlation?

Correlation and causation

Compute It!

Correlation and causation

Scatterplots Revisited

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

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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