Answer true or false to each of the following statements and explain your answers. a. A qualitative predictor variable, whose possible values are represented by three indicator variables, has three possible values. b. In the regression equation y = β0 + β1x1 + β2x2 relating y to a quantitative predictor variable x1 and an indicator variable x2, the regression equations when x2 = 0 and x2 = 1 have different slopes, but the same y-intercepts. c. The method of least squares can be used to obtain estimates of the regression coefficients when there are indicator variables in the regression equation. d. For indicator variables x1 and x2, it is not possible to simultaneously have x1 = 1 and x2 = 1.
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.
Answer true or false to each of the following statements and explain your answers.
a. A qualitative predictor variable, whose possible values are represented by three indicator variables, has three possible values.
b. In the regression equation y = β0 + β1x1 + β2x2 relating y to a quantitative predictor variable x1 and an indicator variable x2, the regression equations when x2 = 0 and x2 = 1 have different slopes, but the same y-intercepts.
c. The method of least squares can be used to obtain estimates of the regression coefficients when there are indicator variables in the regression equation.
d. For indicator variables x1 and x2, it is not possible to simultaneously have x1 = 1 and x2 = 1.
Trending now
This is a popular solution!
Step by step
Solved in 2 steps
