Introduction to Statistics (MAT/SST 115.03 2008S)
You can read the data with
MA = read.csv("/home/rebelsky/Stats115/Data/MarriageAges.csv")
This is a one-sided t-test, which we can express with
You should be able to figure out how tocompute this confidence interval based on The R Notes for Topic 22.
You can produce a similar scatterplot using
You can add the “same age” line with
We can use a one-sample t-test of the difference between the two columns.
t.test(MA$HusbandAge-MA$WifeAge, mu=0, conf.level=.9)
Once again, we need to tell R that this is a one-sided t-test.
t.test(MA$HusbandAge-MA$WifeAge, mu=0, alternative="greater")
We might want to make a normal probability plot to see if the data are normal. I'm not sure why, but R gives a somewhat different plot than does the answer key.
> qqnorm(MA$HusbandAge-MA$WifeAge, datax=T) > qqline(MA$HusbandAge-MA$WifeAge, datax=T)
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