Given a binary dependent variable Yi and independent variables Xki, fill up the space on the left- hand side of the following equations ( 2 points): 1. for the LPM: ()=0+1X1i+2X2i++KXKi 2. for the Logistic regression: ()=0+1X1i+2X2i++KXKi USE THE FOLLOWING DATASET TO ANSWER QUESTIONS 3 AND 4 The dataset "LDVM.xls" contains four variables: - a binary dependent variable "admit": admission into graduate school (1 indicates "admitted", and 0 indicates "not admitted"). - a continuous independent variable "gre": the GRE (graduate record exam) score of the student . a continuous independent variable "gpa": the GPA (grade point average) of the student - a discrete indegendent variahle "rank": prestige of the undergraduate institution, taking on the values 1 through 4. Institutions with a rank of 1 have the highest prestige, while those with a rank of 4 have the lowest.Sheet1Sheet1Sheet1Sheet1Sheet1Sheet1Sheet1This account does not allow editing on your device. about your subscription plan..

1. Given a binary dependent variable Yi and independent variables Xki, fill up the space on the left-
hand side of the following equations ( 2 points): 1. for the LPM: ()=0+1X1i+2X2i++KXKi 2. for the
Logistic regression: ()=0+1X1i+2X2i++KXKi USE THE FOLLOWING DATASET TO ANSWER
QUESTIONS 3 AND 4 The dataset "LDVM.xls" contains four variables: - a binary dependent
variable "admit": admission into graduate school (1 indicates "admitted", and 0 indicates "not
admitted"). - a continuous independent variable "gre": the GRE (graduate record exam) score of
the student . a continuous independent variable "gpa": the GPA (grade point average) of the
student - a discrete indegendent variahle "rank": prestige of the undergraduate institution, taking
on the values 1 through 4. Institutions with a rank of 1 have the highest prestige, while those with a
rank of 4 have the lowest.Sheet1Sheet1Sheet1Sheet1Sheet1Sheet1Sheet1This account does not
allow editing on your device. about your subscription plan.