Isye 6414 Study guides, Class notes & Summaries

ISYE 6414 Final Exam Questions and Answers Already Graded A 1. If there are variables that need to be used to control the bias selection in the model, they should forced to be in the model and not being part of the variable selection process. True 2. Penalization in linear regression models means penalizing for complex models, that is, models with a large number of predictors. True 3. Elastic net regression uses both penalties of the ridge and lasso regression and hence combines the benefits ...

If λ=1 - we do not transform non-deterministic - 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 - The response variable is a ___ variable, because it varies with changes in the predicting variable, or with other changes in the environment fixed - The predicting variable is a ___ variable. It is set fixed, before the response is measured. simple linear regression - regression analysis i...

ISYE 6414 Final Exam Review/111 Questions and answers 2024

ISYE 6414 Final Exam Review/111 Questions and answers 2024

We can assess the constant variance assumption in linear regression by plotting the residuals vs. fitted values. - True If one confidence interval in the pairwise comparison in ANOVA includes zero, we conclude that the two corresponding means are plausibly equal. - True The assumption of normality is not required in linear regression to make inference on the regression coefficients. - False (Explanation: is required) We cannot estimate a multiple linear regression model if the predicting v...

ISYE 6414 - Midterm Exam – 60 Questions and Answers

ISYE 6414 REGRESSION MIDTERM 1 REAL EXAM 2023/2024 What are the variables in regression? -CORRECT ANSWER1. Response (dependent) variable - one particular variable that we are interested in understanding or modelling, such as sales of a particular product. 2. Predicting or Explanatory (independent) variable - set of other variables that we think might be useful in predicting or modelling the response variable (like the price of a product) Which regression variable is a Random variabl...

Least Square Elimination (LSE) cannot be applied to GLM models. - 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. - 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 linear regres...

Assuming that the data are normally distributed, under the simple linear model, the estimated variance has the following sampling distribution: - Chi-squared with n-2 degrees of freedom. The fitted values are defined as? - The regression line with parameters replaced with the estimated regression coefficients. The estimators fo the linear regression model are derived by? - Minimizing the sum of squared differences between the observed and expected values of the response variable. The estim...