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Chapter 7: Scatterplots, Association, and Correlation
Transcript of Chapter 7: Scatterplots, Association, and Correlation
Scatterplots are a type of display that shows the relationship between two quantitative variables. They make it easy to identify trends and patterns amongst the variables.
"r" is always used for correlation
As the x-value increases the y-value also increases
As the x-value increases, the y-value decreases
No relationship among x and y values
"r" is a value between -1 and 1
"r" summarizes the direction and strength of the association for all points
Quantitative Variable Condition:
Both variables must be
Straight Enough Condition:
The form must be "straight enough". Correlation only works with
If an outlier is present, it is your best option to report the correlation
using the outlying point
Correlation ≠ Causation
Correlation is not the same as association. Association is the relationship between two variables. Correlation measures the strength and direction of the linear relationship
Don't correlate categorical variables. Always check the Quantitative Variables Condition
The association must be linear
Just because the correlation coefficent is high does not mean the relationship is linear. Always look at the scatterplot
Beware of outliers. Some outliers can have a huge influence on your correlation coefficient.
Correlation does not equal Causation