What is a Multiple Linear Regression?
Multiple linear regression is a statistical technique in which we have one dependent and several independent variables. Suppose the problem we are looking at can be treated as a problem of one dependent and several independent variables. In that case, it is suitable to use the multiple regression method for data analysis.
Where is linear regression usually used?
An Example Of Multiple Regression Analysis
For example, a researcher wants to examine whether stress level and anxiety level predict test scores. In that case, we have one dependent variable – the exam result, and two independent variables – stress level and anxiety level.
What are the use of null and alternative hypothesis for the Simple Linear Regression?
Therefore, we test the following hypotheses:
Null hypothesis: The stress level and anxiety level do not significantly predict exam scores.
Alternative hypothesis: The stress level and anxiety level significantly predict exam scores.
R function to Compute Multiple Linear Regression
The code to run a Linear Regression using R is as follows:
lm (DV~ IV1 +IV2,+…+IVx data = dataframe)
DV: dependent variable
IV: Independent variables