Logistic regression is similar to linear regression, except that it is used with a categorical response.
True
False
The given statement is TRUE
Logistic Regression is used with a categorical response. For example, response is in the form of true or false.
Logistic regression is similar to linear regression, except that it is used with a categorical response....
Logistic regression is like simple linear or multiple regression in that there is only one DV. a. True b. False
Answer true or false and give justification. 1. Logistic regression cannot be performed after linear PCA. 2. Support vector machine is non-linear classification algorithm. 3. Any regression algorithm can be modified to be used for classification as well.
Decide (with short explanations) whether the following statements are true or false. r) The error term in logistic regression has a binomial distribution s) The standard linear regression model (under the assumption of normality) is not appropriate for modeling binomial response data t Backward and forward stepwise regression will generally provide different sets of selected variables when p, the number of predicting variables, is large. u) BIC penalizes for complexity of the model more than AIC r) The error term...
Logistic regression can be used to predict which customers will respond to a new offer. Is this TRUE or FALSE?
Logistic regression is used when you want to? a. Predict a continuous variable from dichotomous ones. b. Predict a dichotomous variable from continuous or dichotomous variables. c. Predict any categorical variable from other categorical variables. d. Predict a continuous variable from dichotomous or continuous variables.
A regression model that is linear in the unknown parameters is a linear regression model. A) True B) False The test for significance of regression in multiple regression involves testing the hypotheses Ho: B1=B2=B3=0 versus H1: B1≠B2≠B3≠0. A) True B) False The ANOVA is used to test for significance of regression in multiple regression. A) True B) False
machine learning/ stats questions 1. Choose all the valid answers to the description about linear regression and logistic regression from the options below: A. Linear regression is an unsupervised learning problem; logistic regression is a super- vised learning problem. B. Linear regression deals with the prediction of co ontinuous values; logistic regression deals with the prediction of class labe C. We cannot use gradient descent to solve linear regression: we must resort to least square estimation to compute a closed-form...
True or False: Logistic Regression models mean of Y-data as a function of regression variables/parameters
Choose: The logistic regression model shares the following assumption with the “regular” OLS regression model. 1)linear associations 2)normal distribution 3)homoscedasticity 4)homogeneity of variance
4 & 5 QUESTION 4 What is a major difference between linear regression and logistic regression? a. The nature of the independent variable(s) b. The nature of the dependent variable c. The number of independent variables d. The number of dependent variables QUESTION 5 Which one of the following statistical tests would the researcher hope to have a non-significant result (p > .05) in a logistic regression analysis? a. The likelihood ratio test b. The logit step test C. The...