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ISYE 6414 - Midterm Exam Guide: All questions and Solutions Provided $9.99   Add to cart

Exam (elaborations)

ISYE 6414 - Midterm Exam Guide: All questions and Solutions Provided

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  • ISYE 6414
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  • ISYE 6414

ISYE 6414 - Midterm Exam Guide: All questions and Solutions Provided Regression Analysis - ANS Regression analysis is a simple way to investigate the relationship between 2 or more variables in a non-deterministic way. Response/Target Variable (Y) - ANS This is a variable we're interested...

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  • September 11, 2024
  • 11
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • ISYE 6414
  • ISYE 6414
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ISYE 6414 - Midterm Exam
JP


Guide: All questions and
Solutions Provided

, Regression Analysis - ANS Regression analysis is a simple way to investigate the
relationship between 2 or more variables in a non-deterministic way.

Response/Target Variable (Y) - ANS This is a variable we're interested in
understanding, modeling or testing

This is a random variable. It varies with changes in the predictor(s)

2. Predicting/Explanatory (independent) Variables(Xs ~ X1, X2) - ANS These are
variables we think might be useful in predicting or modeling the response variable




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This is a fixed variable. It does not change with the response

Simple Linear Regression - ANS We have a straight line which doesn't fit perfectly to
the points
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The objective is to fit a non-deterministic linear model between the predicting variable
and Y.

In simple linear regression, we have 3 parameters to estimate.

Multiple Linear Regression - ANS We can have a plane if we have two predictions

Polynomial Regression - ANS We are capturing a nonlinear relationship
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Objectives of Linear Regression - ANS 1. Prediction: We want to see how the
response variable behaves in different settings
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2. Modeling: We are interested in modeling the relationship between the response
variable and the explanatory/predicting variables

3. Testing: We are also interested in testing the hypotheses of association relationships.

Simple Linear Regression Assumptions - ANS • Linearity/Mean Zero Assumption: This
means that the expected value of the errors is zero

• Constant Variance Assumption: This means that the variance of the error term is equal
to sigma_squared is the same across all error terms

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