The following multiple regression printout can be used to predict the price (Price) of a used car given how many miles it has on it (Mileage), the size of the engine (Liter), and whether it interior (Leather), where Leather = 1 for cars that have leather interior and 0 otherwise. Regression Analysis: Price Versus Mileage, Liter, Leather Coefficients Term Coef SE Coef T-Value P-Value Constant 6,953 512 13.58 0.000 Mileage -0.0841 0.0174 -4.83 0.000 Liter 3,794 122 31.10 0.000 Leather 1,029 311 3.31 0.001 Regression Equation Price - 6,953 - 0.0841 Mileage + 3,794 Liter + 1,029 Leather (a) Given this Minitab printout, is the response variable in this multiple regression equation a categorical or a numerical variable? numerical O categorical (b) Determine whether the following statement is true or false. Given this Minitab printout, the regression coefficient for miles on the car (Mileage) is statistically significant at a = 0.05. O True O False (c) Determine whether the following statement is true or false. Given this Minitab printout, the regression coefficient for engine size (Liters) is statistically significant at a = 0.05.
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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