In a multiple regression problem involving two independent variables, if b1 is computed to be +2.0, it means that the relationship between X1 and Y is significant the estimated mean of Y increases by 2 units for each increase of 1 unit of X1, holding X2 constant. the estimated mean of Y increases by 2 units for each increase of 1 unit of X1, without regard to X2 the estimated mean of Y is 2 when X1 equals zero.
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.
- In a multiple regression problem involving two independent variables, if b1 is computed to be +2.0, it means that
|
the relationship between X1 and Y is significant |
||
|
the estimated mean of Y increases by 2 units for each increase of 1 unit of X1, holding X2 constant. |
||
|
the estimated mean of Y increases by 2 units for each increase of 1 unit of X1, without regard to X2 |
||
|
the estimated mean of Y is 2 when X1 equals zero. |
Trending now
This is a popular solution!
Step by step
Solved in 2 steps with 2 images
