Isye 641 - Study guides, Class notes & Summaries

Logistic Regression - Answer-Commonly used for modeling binary response data. The response variable is a binary variable, and thus, not normally distributed. In logistic regression, we model the probability of a success, not the response variable. In this model, we do not have an error term g-function - Answer-We link the probability of success to the predicting variables using the g link function. The g function is the s-shape function that models the probability of success with respect to...

ISYE 6414 – Final Exam Questions and Answers 100% Correct Logistic Regression Commonly used for modeling binary response data. The response variable is a binary variable, and thus, not normally distributed. In logistic regression, we model the probability of a success, not the response variable. In this model, we do not have an error term g-function We link the probability of success to the predicting variables using the g link function. The g function is the s-shape function that models the...

ISYE 6414 - Midterm 1 Prep; Questions and Answers 100% Verified If λ=1 Answer-we do not transform non-deterministic Answer-Regression analysis is one of the simplest ways we have in statistics to investigate the relationship between two or more variables in a ___ way random Answer-The response variable is a ___ variable, because it varies with changes in the predicting variable, or with other changes in the environment fixed Answer-The predicting variable is a ___ variable. It is set...

Module 1-3 Midterm, ISYE Summer Midterm, Final, ISYE 6414 - Unit 3 Part 2; Questions and Answers 100% Verified The prediction interval of one member of the population will always be larger than the confidence interval of the mean response for all members of the population when using the same predicting values. (T/F) Answer-True. See 1.7 Regression Line: Estimation & Prediction Examples "Just to wrap up the comparison, the confidence intervals under estimation are narrower than the ...

Regression Analysis - Regression analysis is a simple way to investigate the relationship between 2 or more variables in a non-deterministic way. Response/Target Variable (Y) - 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) - These are variables we think might be useful in predicting or modeling the response variable This i...

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σ^2 (sample distribution of the variance estimator) - is chi-squared distribution with n - 2 degrees of freedom (We lose two degrees of freedom because we replaced the two parameters ß0 and ß1 with their estimators to obtain the residuals.) constant variance assumption - which means that the variance (σ^2) of the error terms or deviances is constant for the given population. A violation of this assumption means that the estimates are not as efficient as they could be in estimating the ...

Least Square Elimination (LSE) cannot be applied to GLM models. - ANS False - it is applicable but does not use data distribution information fully. In multiple linear regression with idd and equal variance, the least squares estimation of regression coefficients are always unbiased. - ANS True - the least squares estimates are BLUE (Best Linear Unbiased Estimates) in multiple linear regression. Maximum Likelihood Estimation is not applicable for simple linear regression and multiple l...

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ISYE 6414 - Unit 4; Questions and Answers 100% Verified In logistic regression, we model the__________________, not the response variable, given the predicting variables. Answer-probability of a success g link function Answer-link the probability of success to the predicting variables 3 assumptions of the logistic regression model Answer-Linearity, Independence, Logit link function Linearity assumption for a Logistic Model Answer-Similar to the regression model we have learned in th...