Does a high value of r2 allow us to conclude that two variables are causally related? Explain. - A high value of r2 can only allow us to conclude that two variables are causally related in linear relationships, but not in nonlinear relationships. - Yes. Regression or correlation analysis always allows us to conclude that two variables are causally related. - A high value of r2 can only allow us to conclude that two variables are causally related in nonlinear relationship
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.
Does a high value of r2 allow us to conclude that two variables are causally related? Explain.
- A high value of r2 can only allow us to conclude that two variables are causally related in linear relationships, but not in nonlinear relationships.
- Yes. Regression or
- A high value of r2 can only allow us to conclude that two variables are causally related in nonlinear relationships, but not in linear relationships.
- No. Regression or correlation analysis can never allow us to conclude that two variables are causally related.
- Yes. Since r2 is the percentage of the total sum of squares that can be explained by using the estimated regression equation, a high value of r2 allows us to conclude that two variables are causally related.
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