Week 4: Logistic Regression Analysis (LRA)LRA can be used when the dependent variable (Y) is binary and the predictors (X1, X2) interval level (or binary). The research question is: Can Y be predicted fromX1and/orX2?Example: Can the passing (1) or failing (0) the MVDA exam (Y) be predicted from the student’s grade on the psychometrics exam (X)?Is there a significant association between grade and passing/failing the exam? (report test statistic, df, and p value)?Here, we look at the Variables in the Equation table at the Wald of the grade. If it’s significant, then yes there is a significant association. An example of how this can be reported: Yes, Wald χ2(1) = 7.090,p=.006Write down the logistic regression equationFor example:if the constant B is -4.200the grade B is: .671Then the equation looks like this:(From now on, sorry for the weird format of the formulas)For what grade is the probability of passing the MVDA exam equal to the probability of failing the MVDA exam?Passing= 50%Failing=50%P=1/2 = In order for to be 1, -4.200+ .671(Grade) has to be equal to 0. This is because e to the power of 0 is 1. So, -4.200 + 0.671(g)=00.671(g)=4.200g=6.259Therefore, the grade where there is an equal chance for passing and failing is 6.259.Calculate the probabilities and odds of passing for X= 0,5, 10X P Odds (rounded up) 0 =0.0148 = = 0.015 5 = 0.3005 = 0.429 10 = 0.9248 =11.5 How to calculate the odds ratio?Example: X P Odds Odds ratio1 .0285 .02931 =1.958 2 .0543 .0574 1.958Therefore, if X increases 1 unit, the odds are...