> x=c(5,3,1,6,4,3,2,6,7)
> y=c(7,4,1,8,5,2,4,7,9)
> mean(x)
[1] 4.111111
> mean(y)
[1] 5.222222
> cor(x,y) # + indicates consistency, more power
[1] 0.943973
> t.test (x,y,paired=T) #sig because of + correlation
Paired t-test
data: x and y
t = -3.1623, df = 8, p-value = 0.01335
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-1.9213584 -0.3008638
sample estimates:
mean of the differences
-1.111111
>
What conclusions can be made regarding statistical significance?
Would that conclusion change with a 1-tailed test? Why or why not?
Conclusion:
The t value of the test is -3.1623 with a p-value < 0.05. So there is suffcient evidence at 5% level of significance to reject the null hypothesis and it can be concluded that there is significant difference in the population means betweeen the dependent populations x and y. The conclusion would not change with a 1-tailed test, because the p-value for the 1-tailed test will be lesser than the p-value of the 2-tailed test by 50%. So the reduction in p-value further would not change the decision of rejection in this case.
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