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Chapter 15: Correlation - Coggle Diagram
Chapter 15: Correlation
Correlation is a statistical technique that is used to measure and describe the relationship between two variables.
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The pairs of scores can be listed in a table, or they can be presented graphically in a scatter plot.
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The Pearson correlation measures the degree and the direction of the linear relationship between two variables.
The Pearson correlation for a sample is identified by the letter r. The corresponding correlation for the entire population is identified by the Greek letter rho(p).
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With a perfect linear relationship, every change in the X variable is accompanied by a corresponding change in the Y variable.
A measure of the degree of covariability between two variables; the degree to which they vary together is known as the sum of products (SP).
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The signs (+1 and −) are critical in determining the sum of products, SP.
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When you encounter correlations, there are four additional considerations that should be kept in mind.
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One or two extreme data points, often called outliers, can have a dramatic effect on the value of a correlation.
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When judging how “good” a relationship is, it is tempting to focus on the numerical value of the correlation.
When establishing a cause-and-effect relationship, it is necessary to conduct a true experiment in which one variable is manipulated by a researcher and other variables are rigorously controlled
An outlier is an individual with X and/or Y values that are substantially different can be (larger or smaller) from the values obtained for the other individuals in the data set
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A partial correlation measures the relationship between two variables while controlling the influence of a third variable by holding it constant.
Partial correlation measures the relationship between two variables while controlling the influence of a third variable.
