I have created a T test in R and got the below output.
t.test(casein,mu=pw,alternative="greater") ## One Sample t-test ## ## data: casein ## t = 3.348, df = 11, p-value = 0.003251 ## alternative hypothesis: true mean is greater than 261.3099 ## 95 percent confidence interval: ## 290.1791 Inf ## sample estimates: ## mean of x ## 323.5833 Here as you can see the P-value is 0.003, which is less than the significant value of 0.05. Hence shouldn't the alternative hypothesis be rejected in this case? How is true?
Best Answer
The purpose of the t.test() function is to return the p-value, a confidence interval and a some summary statistics. That is what it has done.
It is up to you do decide what you want do with the results. If you think that p = 0.003 is sufficiently small to reject the null hypothesis, then that is your business.
Note that it is always the null hypothesis (that mu=pw) that is accepted or rejected, not the alternative. The alternative hypothesis (that mu>pw) is, as the name implies, the alternative when the null become untenable.