Estimation error - Study guides, Revision notes & Summaries

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...

Intuition of the Black-Derman-Toy interest rate model - ANSWER-Observed spot rates drive rate levels while implied rate volatilities drive rate spreads Understanding the intuition of imposing these two conditions helps in understanding the essence of the BDT model. The spot rates in the currently observed term structure drive the overall levels of the rates that are projected throughout the binomial tree. The implied volatilities of options trading on short‐term rates (i.e., interest rate c...

ISYE 6414 Final Exam; Questions and Answers 100% Verified Logistic regression is different from standard linear regression in that: Answer-It does not have an error term; The response variable is not normally distributed; It models probability of a response and not the expectation of the response Logistic regression models Answer-The probability of a success given a set of predicting variables In logistic regression Answer-The estimation of the regression coefficients is based on m...

Doubling the size of the sample will reduce the standard error of the mean The sample mean is the point estimator of U A simple random sample of size n from an infinite population of size N is to be selected. Each possible sample should have the same probability of being selected Which of the following statements regarding the sampling distribution of sample means is incorrect? The standard deviation of the sampling distribution is the standard deviation of the populatio...

When is a t-test used instead of a z-test? Ans- when the population standard deviation is unknown. Which of the following is one of the requirements of a one-sample t-test? Ans- the population standard deviation is estimated by computing the estimated standard error of the mean. Which of the following requirements is common to both the z-test and the onesample t-test? Ans- there is one random sample of interval or ratio scores. Which of the following would make it more likely your t-tes...

In logistic regression, we model the__________________, not the response variable, given the predicting variables. - probability of a success g link function - link the probability of success to the predicting variables 3 assumptions of the logistic regression model - Linearity, Independence, Logit link function Linearity assumption for a Logistic Model - Similar to the regression model we have learned in the previous lectures, the relationship we assume now, between the link, the g of ...

Logistic regression, we model the__________________, not the response variable, given the predicting variables. correct answers probability of a success g link function correct answers link the probability of success to the predicting variables 3 assumptions of the logistic regression model correct answers Linearity, Independence, Logit link function Logistic Model: Linearity assumption correct answers Similar to the regression model we have learned in the previous lectures, the relatio...

Intuition of the Black-Derman-Toy interest rate model - ANSWER-Observed spot rates drive rate levels while implied rate volatilities drive rate spreads Understanding the intuition of imposing these two conditions helps in understanding the essence of the BDT model. The spot rates in the currently observed term structure drive the overall levels of the rates that are projected throughout the binomial tree. The implied volatilities of options trading on short‐term rates (i.e., interest rate c...

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...

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. - true See 1.7 Regression Line: Estimation & Prediction Examples "Just to wrap up the comparison, the confidence intervals under estimation are narrower than the prediction intervals because the prediction intervals have additional variance from the variation of a new measurement." In ANOV...