WK3 Project Assignment Download Admissions.xlsx data set here . It shows graduate program admission decisions (Yes: 1 and No: 2), GRE score and undergraduate GPA (1: ≥ 3.5 and 2:

Must be completed using MiniTab program. Questions needing to be answered are: 1. Evaluate the goodness of fit of the model. 2. Determine the significance of indenendent variables. 3. Interpret odds ratios for independent variables. 4. State the binary logistic regression equation. 5. Evaluate the classification accuracy of the model. and 6. Check if the residuals are independent.


WK3 Project Assignment Download Admissions.xlsx data set here . It shows graduate program admission decisions (Yes: 1 and No: 2), GRE score and undergraduate GPA (1: ≥ 3.5 and 2: < 3.5)="" for="" fifty="" students.="" tasks:="" fit="" a="" binary="" logistic="" regression="" model="" with="" admission="" decision="" as="" the="" dependent="" variable,="" gre="" and="" gpa="" as="" the="" independent="" variables.="" ·="" evaluate="" the="" goodness="" of="" fit="" of="" the="" model.="" ·="" determine="" the="" significance="" of="" independent="" variables.="" ·="" interpret="" odds="" ratios="" for="" independent="" variables.="" ·="" state="" the="" binary="" logistic="" regression="" equation.="" ·="" evaluate="" the="" classification="" accuracy="" of="" the="" model.="" ·="" check="" if="" the="" residuals="" are="" independent.="" submission="" details:="" ·="" submit="" a="" 3–4="" page="" microsoft="" word="" document,="" using="" apa="" style.="" ·="" the="" relevant="" minitab="" output="" should="" be="" copied="" to="" this="" document.="" wk3="" project="" assignment="" download="" admissions.xlsx="" data="" set="" here="" .="" it="" shows="" graduate="" program="" admission="" decisions="" (yes:="" 1="" and="" no:="" 2),="" gr="" e="" score="" and="" undergraduate="" gpa="" (1:="3.5" and="" 2:="">< 3.5)="" for="" fifty="" students.="" tasks:="" fit="" a="" binary="" logistic="" regression="" model="" with="" admission="" decision="" as="" the="" dependent="" variable,="" gre="" and="" gpa="" as="" the="" independent="" variables.="" ·="" evaluat="" e="" the="" goodness="" of="" fit="" of="" the="" model.="" ·="" determine="" the="" significance="" of="" independent="" variables.="" ·="" interpret="" odds="" ratios="" for="" independent="" variables.="" ·="" state="" the="" binary="" logistic="" regression="" equation.="" ·="" evaluate="" the="" classification="" accuracy="" of="" the="" model.="" ·="" check="" if="" the="" residua="" ls="" are="" independent.="" submission="" details:="" ·="" submit="" a="" 3="" –="" 4="" page="" microsoft="" word="" document,="" using="" apa="" style.="" ·="" the="" relevant="" minitab="" output="" should="" be="" copied="" to="" this="" document.="" wk3="" project="" assignment="" download="" admissions.xlsx="" data="" set="" here="" .="" it="" shows="" graduate="" program="" admission="" decisions="" (yes:="" 1="" and="" no:="" 2),="" gre="" score="" and="" undergraduate="" gpa="" (1:="3.5" and="" 2:="">< 3.5) for fifty students. tasks: fit a binary logistic regression model with admission decision as the dependent variable, gre and gpa as the independent variables.  evaluate the goodness of fit of the model.  determine the significance of independent variables.  interpret odds ratios for independent variables.  state the binary logistic regression equation.  evaluate the classification accuracy of the model.  check if the residuals are independent. submission details:  submit a 3–4 page microsoft word document, using apa style.  the relevant minitab output should be copied to this document. 3.5)="" for="" fifty="" students.="" tasks:="" fit="" a="" binary="" logistic="" regression="" model="" with="" admission="" decision="" as="" the="" dependent="" variable,="" gre="" and="" gpa="" as="" the="" independent="" variables.="" ="" evaluate="" the="" goodness="" of="" fit="" of="" the="" model.="" ="" determine="" the="" significance="" of="" independent="" variables.="" ="" interpret="" odds="" ratios="" for="" independent="" variables.="" ="" state="" the="" binary="" logistic="" regression="" equation.="" ="" evaluate="" the="" classification="" accuracy="" of="" the="" model.="" ="" check="" if="" the="" residuals="" are="" independent.="" submission="" details:="" ="" submit="" a="" 3–4="" page="" microsoft="" word="" document,="" using="" apa="" style.="" ="" the="" relevant="" minitab="" output="" should="" be="" copied="" to="" this="">