ISYE 6414 - Midterm Exam 2025 update
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Terms in this set (60)
Regression analysis is a simple way to investigate the
Regression Analysis relationship between 2 or more variables in a non-
deterministic way.
This is a variable we're interested in understanding,
modeling or testing
Response/Target Variable
(Y)
This is a random variable. It varies with changes in the
predictor(s)
These are variables we think might be useful in
2. Predicting/Explanatory predicting or modeling the response variable
(independent)
Variables(Xs ~ X1, X2) This is a fixed variable. It does not change with the
response
, We have a straight line which doesn't fit perfectly to
the points
The objective is to fit a non-deterministic linear model
Simple Linear Regression
between the predicting variable and Y.
In simple linear regression, we have 3 parameters to
estimate.
Multiple Linear Regression We can have a plane if we have two predictions
Polynomial Regression We are capturing a nonlinear relationship
1. Prediction: We want to see how the response
variable behaves in different settings
2. Modeling: We are interested in modeling the
Objectives of Linear
relationship between the response variable and the
Regression
explanatory/predicting variables
3. Testing: We are also interested in testing the
hypotheses of association relationships.
|comprehensive questions and verified answers
(complete solutions) ASSURED SUCCESS|GRADE
A+!!
Save
Terms in this set (60)
Regression analysis is a simple way to investigate the
Regression Analysis relationship between 2 or more variables in a non-
deterministic way.
This is a variable we're interested in understanding,
modeling or testing
Response/Target Variable
(Y)
This is a random variable. It varies with changes in the
predictor(s)
These are variables we think might be useful in
2. Predicting/Explanatory predicting or modeling the response variable
(independent)
Variables(Xs ~ X1, X2) This is a fixed variable. It does not change with the
response
, We have a straight line which doesn't fit perfectly to
the points
The objective is to fit a non-deterministic linear model
Simple Linear Regression
between the predicting variable and Y.
In simple linear regression, we have 3 parameters to
estimate.
Multiple Linear Regression We can have a plane if we have two predictions
Polynomial Regression We are capturing a nonlinear relationship
1. Prediction: We want to see how the response
variable behaves in different settings
2. Modeling: We are interested in modeling the
Objectives of Linear
relationship between the response variable and the
Regression
explanatory/predicting variables
3. Testing: We are also interested in testing the
hypotheses of association relationships.
