7648588767 A study conducted at Baystate Medical Center in Springfield, M giving

Question

7648588767 A study conducted at Baystate Medical Center in Springfield, M giving birth to a low-birth-weight baby. Low birth weight is defined as weighing fewer than 2,500 grams (5 pounds, 8 ounces) at birth. Low-birth-weight babies have increased risk of health problems, disability, and death. [Source etts, identified factors that affect the risk of Suppose that you conduct a similar study focusing on the age, prepregnancy weight, and weight gain of the mothers as predictors of their babies' birth weight among 50 low-birth-weight babies. You use a statistical software package to run a multiple regression predicting birth weight in grams (BIRTHWT) from the mother's age in years (AGE), the mother's prepregnancy weight in pounds (MOMWT), and the mother's weight gain in pounds (GAIN). Use the output Model Summary Adjusted R Std. Error of the Model Square 0.157 Estimate 0.457a 0.208 360.352 ANOVA Model Two-Tailed Sig. 524 1930 1572579.1 5973256.5 7545835.6 Residual b. Dependent Variable: BIRTHWT Coefficientse 1 (Constant)

Explanation / Answer

The Estimated Regression Equation is:

Y^=2790.67-32.30*AGE-0.89*MOMWT+5.68*GAIN

The overall regression model was significant at 5% level of significance, F[(3,46)]=4.037,p=0.0125, R square=0.208.

Only AGE was the significant predictor of birth weight (t=-2.9423,p=0.0051)

Suppose that the coefficients of of all predictor variables in the model are significant.

Comparing the magnitudes of the standard errors of the coefficients gives us the best predictor variable. The coefficients whose standard error is lese is the best predictor.

If our objective is given in this problem then we should have the following:

The sample should be a representative sample of pregnant women that includes women who gave birth to normal weight babies, not only the women who gave birt to low-birth-weight babies.

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