R语言吸烟者假设检验数据分析可视化案例分析报告(附代码数据)

R语言吸烟者假设检验数据分析案例分析报告加载#download.file("/stat/data/nc.RData",destfile="nc.RData")load("nc.RData")这个数据集有什么情况？我们的样本中有多少个案例summary(nc)Categorical:

Maturity,premie,marital,lowbirthweight,gender,habit.whitemom

Numerical:

fage,mage,weeks,gained,visits,weight.对于数值变量，是否有异常值？par(mfrow=c(3,2))hist(nc$fage)hist(nc$mage)hist(nc$weeks)hist(nc$gained)hist(nc$visits)hist(nc$weight)你可以看到，重量和周数低的离群值和访问具有很高的异常值。做一个并排boxplot。强调这两个变量之间的关系是什么？boxplot(nc$weight~nc$habit,data=nc,col="lightblue")吸烟者似乎有重量较轻的婴儿。检查是否满足推理所需的条件。请注意，您将需要获取样本大小以检查条件。您可以使用上面的命令来计算组大小，但是用长度替换平均值。len<-by(nc$weight,nc$habit,length)len##nc$habit:nonsmoker##[1]873##--------------------------------------------------------##nc$habit:smoker##[1]126len>30##nc$habit##nonsmokersmoker##TRUETRUE如果吸烟和不吸烟母亲所生的婴儿的平均体重不同，则写出测试的假设。library(openintro)library(BHH2)inference(y=nc$weight,x=nc$habit,est="mean",type="ht",null=0,alternative="twosided",method="theoretical")##Responsevariable:numerical,Explanatoryvariable:categorical##Differencebetweentwomeans##Summarystatistics:##n_nonsmoker=873,mean_nonsmoker=7.1443,sd_nonsmoker=1.5187##n_smoker=126,mean_smoker=6.8287,sd_smoker=1.3862##Observeddifferencebetweenmeans(nonsmoker-smoker)=0.3155####H0:mu_nonsmoker-mu_smoker=0##HA:mu_nonsmoker-mu_smoker!=0##Standarderror=0.134##Teststatistic:Z=2.359##p-value=0.0184将类型参数改为“ci”，构造并记录吸烟与不吸烟母亲所生婴儿体重之间差异的置信区间。inference(y=nc$weight,x=nc$habit,est="mean",type="ci",null=0,alternative="twosided",method="theoretical",order=c("smoker","nonsmoker"))##Responsevariable:numerical,Explanatoryvariable:categorical##Differencebetweentwomeans##Summarystatistics:##n_smoker=126,mean_smoker=6.8287,sd_smoker=1.3862##n_nonsmoker=873,mean_nonsmoker=7.1443,sd_nonsmoker=1.5187##Observeddifferencebetweenmeans(smok