In: Statistics and Probability
Question 4
Which of these are examples of binary response models
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Question 5
When comparing the possible advantages and disadvantages of the Logistical (Logit) Models versus the Linear Probability Models (LPM), which is true?
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We have to answer the above questions:-
Question (1)
# Which of these are examples of binary response models
Answer:-
From all options given to the question,Option (a) is correct answer
" using income (measured in dollars) to predict the probability of whether or not someone buys a house "
Explanation:- As we want to identify the binary response models i.e the model in which response is on the binary scale("yes/no" , " 0 / 1 ",etc).So In option a :: using income (continuous) variable we can predict the probability of house purchasing(Classify values from 0 - 0.5 as 0 and 0.5 - 1 as 1).Hence in this sense our response will become binary(0/1)
Question (2)
# When comparing the possible advantages and disadvantages of the Logistical (Logit) Models versus the Linear Probability Models (LPM), which is true?
Answer:-
Among the options given the correct one is option (a) is correct.
" LPM can be completed using Excel data analysis regression function, while Logit Models cannot "
Explanation:-
If you want to compute the LPM you can use Excel Data Analysis Pack's regression function but we dont have option to perform analysis on Logistical Model(Logit model) in it.To perform Logit analysis we need to install XLSTAT for your current Excel version and then only you can perform LOgit analysis in Excel otherwise not.
So,In this way option (A) is the only correct answer.