The data set hemorrhage.sav contains a sample of 100 low birth weight infants born in Boston, Massachusetts. Germinal matrix hemorrhage (gmh) is a dichotomos variable that coded as 1 if the baby had a hemorrhage and 0 if the baby did not have a hemorrhage. (See the attached image)You wish to know if gestational age, systolic blood pressure (sbp), and gender predicts hemorrhage. What are the null and alternative hypotheses for this analysis? (hint: there should be 4 sets) Is the model as a whole significant? How do you know?Regardless if the variables are significant interpret the odds ratio for gender, sbp, and gestational age. ### Model SummaryThis section presents a summary of the logistic regression model's fit.#### Step 1:- **-2 Log likelihood**: 76.165- **Cox & Snell R Square**: 0.166- **Nagelkerke R Square**: 0.271*Note*: Estimation terminated at iteration number 6 due to minimal parameter estimate changes.### Hosmer and Lemeshow TestThis test assesses the goodness of fit for the logistic regression.#### Step 1:- **Chi-square**: 10.418- **Degrees of freedom (df)**: 8- **Significance (Sig.)**: 0.237### Omnibus Tests of Model CoefficientsThis test evaluates the overall significance of the model.#### Chi-square for all Criteria (Step, Block, Model):- **Chi-square**: 18.114- **df**: 3- **Significance (Sig.)**: 0.000### Variables in the EquationThis table details the variables included in the model and their coefficients.| Variable | B | S.E. | Wald | df | Sig. | Exp(B) | 95% C.I. for EXP(B) Lower | Upper ||------------------------|--------|-------|-------|----|-----|--------|--------------------------|-------|| Systolic blood pressure| -0.045 | 0.029 | 2.437 | 1 | 0.119 | 0.956 | 0.903 | 1.012 || Baby's gender (1) | 1.215 | 0.648 | 3.519 | 1 | 0.061 | 3.370 | 0.947 | 11.995|| Gestational age | -0.315 | 0.134 | 5.559 | 1 | 0.018 | 0.730 | 0.561 | 0.948 || Constant | 8.616 | 3.610 | 5.696 | 1 | 0.017 | 5516.878| | |*Note*: Variables entered in step 1 include systolic blood pressure, baby's gender, and gestational age.###

1. The task is to test the association between the variables. Ho : β0=β1=β2=β3H1 : At least two of the β's are not equal.Ho1 : There is no association between gestational age and hemorrhage.H11 : There is an association between them.Ho2 : There is no association between sbp and hemorrhage.H12 : There is an association between them.Ho3 : There is no association between gener and hemorrhage.H13 : There is an association between them. 2. The p-value of the above test is 0.237. According to the decision rule, null hypothesis must be rejected when p-value is less than the alpha level of significance. 0.237 > 0.05 - Accept Ho Concluding that the regression coefficients are equal. 3. The odd's ratio for logistic regression are calculated using the formula : r=exp(coefficients) The odd's ratio for gender, systolic blood pressure and gestational age are given as : Odd's ratio for gender (r1) =e1.215=3.370Odd's ratio for sbp (r2) =e-0.045=0.956Odd's ratio for gestational age (r3) =e-0.315=0.730