Basic Linear Regression Model
While testing for a Basic Linear regression model, the following variables are considered for analysis. NUMBER_LAYERS - Collapsing it into a binary categorical Explanatory variables with 2 levels.
DEPTH_RIMFLOOR_TOPOG - Quantitative Response variable
Code:
Results:
Comments:
means summary response gives the output as per the different NUMBER_Layers. The aggregate mean is 0.83 As per the GLM model we see that :
Number of Observations Read : 384343
Number of Observations Used: 384343
Response variable used here is DEPTH_RIMFLOOR_TOPOG .
F- statistics value is 3011.12
P-Value is .0001 ( i.e negligible. so we can reject the null hypothesis).
R- square value is 0.007774
The mean of depth - 0.075838 i.e almost equal to that of the summary table mean value.
Parameter estimates:
The Beta Sub zero value : 0.75538
The Beta Sub one Value : 1.27646
So the Depth rate (0) = 0.75538 + 1.27646 * Depth (0) = 0.75538
Depth rate (1) = 0.75538 + 1.27646 * Depth (1) = 2.03
