Statistical Analysis of Factors Affecting Birth Weight: A Chi-Squared, Regression, and ANOVA Approach

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Statistical Analysis of Factors Affecting Birth Weight: A Chi - Squared, Regression, and ANOVA Approach objective: to ensure that students are able to perform chi - squared, regression, and ANOVA analyses Download a copy of the data file: phbirth.dat col 3 - years of education col 4 - mother smoked col 5 - gestation (in weeks) col 6 - birth weight (in grams) All tests are to be done with a significance level of 0.05. 1. Investigate the relationship between smoking and birth weight. Define low birth weight as less than 3000 grams. Analyze columns 4 and 6, and report whether you found evidence that a mother's smoking habit could be associated with low birth weight. Solution . We can conduct a Chi - squared test. From the given data, we can form the following contingency table Birth weight <3000g Birth weight >=3000g Smoking 124 145 Non - smoking 216 630 Step 1: Set up two h ypotheses Null hypothesis H0: A mother's smoking habit could not be associated with low birth weight. Alternative hypothesis Ha: A mother's smoking habit could be associated with low birth weight. Step 2: Level of significance 05 . 0 =  Step 3: Decision rule If the p - value is less than or equal to 05 . 0 =  , then we reject H0. Step 4: Test statistic and p - value
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