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…

Answered: The data set hemorrhage.sav contains a…

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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 Summary
This 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 Test
This 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 Coefficients
This 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 Equation
This 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.

###

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