Correlation and regression are two closely related topics in statistics. For each of the following statements, indicate whether the statement is true of correlation, true of regression, true of both correlation and regression, or true of neither correlation nor regression. Regression Correlation Both Correlation and Regression Neither Correlation nor Regression Can tell you whether one variable (such as smoking) causes another (such as cancer) Provides a way to predict a specific value of one variable (such as weight) from the value of another variable (such as height) Can be tested for statistical significance
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
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Regression
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Correlation
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Both Correlation and Regression
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Neither Correlation nor Regression
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| Can tell you whether one variable (such as smoking) causes another (such as cancer) |
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| Provides a way to predict a specific value of one variable (such as weight) from the value of another variable (such as height) |
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| Can be tested for statistical significance |
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