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

A statistical analysis of factors affecting birthweight, using chi-squared tests, regression, and ANOVA methods.

Olivia Smith
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Statistical Analysis of Factors Affecting Birth Weight: A Chi-Squared, Regression,and ANOVA Approachobjective:to ensure that students are able to performchi-squared, regression, and ANOVA analysesDownload a copy of the data file:phbirth.datcol 3-years of educationcol 4-mother smokedcol 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 habitcould be associated with low birth weight.Solution. We can conduct a Chi-squared test. From the given data, we can form the followingcontingency tableBirth weight <3000gBirth weight >=3000gSmoking124145Non-smoking216630Step 1:Set up two hypothesesNull hypothesisH0: Amother's smoking habit couldnotbe associated with low birth weight.Alternative hypothesisHa: Amother's smoking habit could be associated with low birth weight.Step 2:Level of significance05.0=Step 3: Decision ruleIf the p-value is less than or equal to05.0=, then we reject H0.Step 4:Test statistic and p-value

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Subject
Statistics

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