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Hosmer and Lemeshow cited a study conducted at Baystate Medical Center in Springfield, Massachusetts, to identify factors that affect the risk of 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. Data were collected on 189 women, 59 of whom had low birth weight babies and 130 of whom had normal-birth-weight babies. (Hosmer, D. W, & Lemeshow, S. (2000). Applied Logistic Regression, 2nd ed. Hoboken: Wiley. 25) Suppose you use a subsample of these data to estimate a least squares regression line predicting the baby's birth weight (in grams) from the mom's age and the mom's prepregnancy weloht (in pounds). In the subsample, the mean birth weight is 2884 grams, with a standard deviation of 32/13; the mean of the mom's age is 27.14 years, with a standard deviation of 5.37; and the mean of morn's prepregnancy weight is 149.86 pounds, with a standard deviation of 31.36. The zero-order (Pearson) correlation between the baby's birth weight and the mom's age is -0.60, between the baby's birth weight and the mom's prepregnancy weight is -0.32, and between the mom's age and the mom's prepregnancy weloht is 0.74. You will use the given values to compute the partial slopes of the repression equation. Before you beqin, complete the following table tu siria the values provided. Call the mom's age X; and the mom's prepregnancy welght Xy Relevant information Needed for Computing Partial Slopes for a Multiple Regression Equation Baby's Birth Weight Carams) Mom's Apetyears) Mom's Prepregnancy Weight (pounds) X- Zero Order Correlations Tyl 12 119- Compute the partial slopes and the intercept for the regression equation to predict the baby's birth weight from the mom's age (X) and the mom's prepregnancy weight (X). Using your calcutations, complete the following estimated regression equation (Equation A) Y- X + ( _X for every Increase in the mom's, the baby's This equation suggests that among moms of the same predicted birth weight

(Equation A) Y- +()Xi+ ( ) This equation suggests that among moms of the same predicted birth weight by for every Increase in the mom's age, the baby's Using this equation, you would predict that a baby's birth weight born from a mom who li 23 years old and has a prepregnancy weight of 161 pounds will be Suppose your estimated regression equations (Equation B) Y = (2,531,32) + (2013) (X) + (-0,21) (X) Equation suggests that among moms of the same predicted birth weight for every Increase in the mom's age, the baby Using Equation you would predict that baby's birth weight born from a mori who is 23 years old and has a prepregnancy welont of 101 pounds will be