BIOT 6214 Assignment 11_Swara Ragalwar
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Dec 6, 2023
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BIOT 6214
NAME Swara Ragalwar
Assignment #11
1.
Perform multivariable regression using JMP. Summarize regression result in addition to screenshots from regression result. Data can be found in Canvas, Problem 11-1
Solution:
By performing JMP analysis we get
To get the highest R
2
adj value we remove the significant variables in the following order.
We first remove x1 which gives us a value of 0.9784 which is an increase from the existing value
of 0.976.
Upon removing the next least significant terms x1*x2 and x1*x3 we find that the R
2
adj value
decreases to 0.977.
R
2
adj value decreases after the last removal, hence we undo it to get the highest value of R
2.
.
The higher the R
2 adj value the better the model, hence by performing multivariable analysis
using JMP we find out the best model.
The P value of F-Test shows a significance of effect that the model predicts. p < a means that the
effect is significant.
2.
Perform multivariable regression using JMP. Summarize regression result in addition to screenshots from regression result. Data can be found in Canvas, Problem 11-2
Solution:
By performing JMP analysis we get.
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To get the highest R
2 adj value we remove the significant variables in the following order.
We first remove Load*Flow which gives us a value of 0.9508 which is an increase from the
existing value of 0.9420. We then remove the second term Flow*Mud which increases the R
2 adj
value to 0.9515.
Upon removing the next least significant terms Load*speed we find that the R
2
adj value
decreases to 0.947.
R
2
adj value decreases after the last removal, hence we undo it to get the highest value of R
2.
.
The higher the R
2 adj value the better the model, hence by performing multivariable analysis
using JMP we find out the best model with an R
2 adj value 0.9515 and R square value 0.971.
The P value of F-Test shows a significance of effect that the model predicts. p < a means that the
effect is significant.
3.
In a regression, p value of an effect is 0.001, less than the level of significance (alpha = 0.05). This
means that (choose all that apply)
a.
The effect is significant.
b.
Its coefficient is not zero.
c.
The effect can be ignored.
d.
Its coefficient is zero
Solution:
The right options are.
a.
The effect is significant.
b.
Its coefficient is not zero.
4.
What is the difference between simple linear regression and multiple regression? a.
Simple linear regression only uses one independent variable, while multiple regression
uses more than one independent variable. b.
Simple linear regression only works with categorical independent variables, while multiple regression works with continuous independent variables c.
Simple linear regression is used for identification of outlier, while multiple regression is used for prediction.
d.
Simple linear regression assumes a linear relationship between the dependent variable and the independent variable, while multiple regression allows for multiple independent
variables with potentially nonlinear relationships Solution:
The correct difference between simple linear regression and multiple regression
a.
Simple linear regression only uses one independent variable, while multiple regression uses more than one independent variable. 5.
What is the purpose of the F-test in multiple regression? a.
To test for the significance of the individual independent variables
b.
To test for the significance of the intercept term c.
To test for the overall significance of the model d.
To test for multicollinearity among the independent variables Solution
The purpose of F-test in multiple regression is. c. To test the overall significance of the model.
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