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[Show more]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-Lineari...
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Add to cartIn 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-Lineari...
The _______________ for multiple linear regression do not have constant variance. - Answer-sample 
residuals 
The ______________ for multiple linear regression have constant variance. - Answer-error terms 
QQPlot and histogram are used to assess what in MLR? - Answer-normality 
Residuals vs predicto...
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Add to cartThe _______________ for multiple linear regression do not have constant variance. - Answer-sample 
residuals 
The ______________ for multiple linear regression have constant variance. - Answer-error terms 
QQPlot and histogram are used to assess what in MLR? - Answer-normality 
Residuals vs predicto...
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 ...
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Add to cartIf 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 ...
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-fu...
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Add to cartLogistic 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-fu...
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. - Answer-True 
2. Penalization in linear regression models means penalizing for complex models, that is, models with...
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Add to cart1. 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. - Answer-True 
2. Penalization in linear regression models means penalizing for complex models, that is, models with...
Least Square Elimination (LSE) cannot be applied to GLM models. - Answer-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. - Answer-...
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Add to cartLeast Square Elimination (LSE) cannot be applied to GLM models. - Answer-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. - Answer-...
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