Normal or Parametric Data

data.new ← Read.table(“tmp.data.head”, header=TRUE)
t.test(data.new[,2])
        One Sample t-test
data:  data.new[, 2]
t = 2876.076, df = 41, p-value < 2.2e-16
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
 11.05714 11.07268
sample estimates:
mean of x
 11.06491

What does this mean? The data is highly significantly different from zero.

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Transcript

So let us take a look at those measurements again. Now, not of the cup but of the femoral head - it's the little ball that goes into the cop in a prosthetic hip.

And, in this case, we read our data in, and now we're going to compute a one sample t-test. So to do this, we got our data, and we get our values. And what does this tell us? The result of the t-test using this data tells us that our p-value is 2.2 times 10^^-16. And the alternative hypothesis is that the true mean is not equal to zero. The 95% confidence interval is 11.05714 to 11.07268. And the mean is 11.06491. Well, what does that mean? Well, that means the data here says that the true meaning is not equal to zero. That is our hypothesis is that it's highly significantly different from zero - so the data isn't zero. That's not surprising because the mean of the data is up around 11 millimeters.