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ISYE 6414 - UNIT 2 EXACTITUDE EXAM SOLUTIONS 2024 (100% PASS!) $12.49   Add to cart

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ISYE 6414 - UNIT 2 EXACTITUDE EXAM SOLUTIONS 2024 (100% PASS!)

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  • July 26, 2024
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  • ISYE 6414 - UNIT 2
  • ISYE 6414 - UNIT 2
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ISYE 6414 - UNIT 2 EXACTITUDE EXAM SOLUTIONS 2024 (100% PASS!)
What are the assumptions for multiple linear regression? - Precise Answer ✔✔Linearity/Mean zero assumption, Constant Variance, Independence and Normality (for statistical inference)
what are the model parameters to be estimated in MLR? - Precise Answer ✔✔B0 (intercept), B1-Bp, and sigma squared
In multiple linear regression, the model can be written in...? - Precise Answer ✔✔Matrix form.
design matrix - Precise Answer ✔✔a matrix consisting of columns of predicting variables including the column of ones corresponding to the intercept:
simple linear regression - Precise Answer ✔✔linear regression with one quantitative predicting variable
ANOVA - Precise Answer ✔✔linear regression with one or more qualitative predicting variables
Multiple linear regression - Precise Answer ✔✔multiple quantitative and qualitative predicting variables in MLR, the sampling distribution for sigma^2 is MSE ..... - Precise Answer ✔✔chi-
square with n-p-1 DF
marginal model (SLR) - Precise Answer ✔✔captures the association of one predicting variable to the response variable marginally, that means without consideration of other factors.
conditional model (MLR) - Precise Answer ✔✔captures the association of a predictor variable to the response variable, conditional of other predicting variables in the model.
We can make causality statements for... - Precise Answer ✔✔experimental designs
We can make associated statements for... - Precise Answer ✔✔observational studies
3 ways Predicting Variables can be distinguished as: - Precise Answer ✔✔Controlling, Explanatory, Predictive
Controlling factors - Precise Answer ✔✔to control for bias selection in the sample. They are used as 'default' variables in order to capture more meaningful relationships.
Explanatory factors - Precise Answer ✔✔to explain variability in the response variable; they may be included in the model even if other "similar" variables are in
the model

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