Which of the following is false concerning the interpretation of a regression equation expressing the relationship between variables X and Y? A) The beta coefficient predicts a per unit increase in Y based on X B) The regression equation is typically adapted to populations beyond the observed range for X C) Regression equations are strongly influenced by the presence of outliers D) Regression equations only describe linear relationships between two variables
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.
Which of the following is false concerning the interpretation of a regression equation expressing the relationship between variables X and Y?
-
A) The beta coefficient predicts a per unit increase in Y based on X
-
B) The regression equation is typically adapted to populations beyond the observed
range for X
C) Regression equations are strongly influenced by the presence of outliers
D) Regression equations only describe linear relationships between two variables
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