Single Sample t-test Hypothesis Confusion

Question

In case you want data

set.seed(100)
hotel <- rep(1,100)
hotel <- unlist(lapply(hotel, function(x) { runif(1,1,5) } ))

NULL Hypothesis :- Hotel rating is greater or equal to 3

ALTERNATE Hypothesis :- Hotel rating is less than 3

 t.test(hotel, mu = 3, alternative = 'less')

        One Sample t-test

data:  hotel
t = 0.76629, df = 99, p-value = 0.7773
alternative hypothesis: true mean is less than 3
95 percent confidence interval:
     -Inf 3.254185
sample estimates:
mean of x 
 3.080266

According to this output I fail to reject NULL Hypothesis in favor of alternate Hypothesis.

Here the t-test is suggesting that data is in favor of hypothesis that hotel rating is >=3

But Suppose In case I reversed My hypothesis NULL Hypothesis :- Hotel rating is less than or equal to 3 Alternative :- Hotel rating is greater than 3

t.test(hotel, mu = 3, alternative = 'greater')

        One Sample t-test

data:  hotel
t = 0.76629, df = 99, p-value = 0.2227
alternative hypothesis: true mean is greater than 3
95 percent confidence interval:
 2.906346      Inf
sample estimates:
mean of x 
 3.080266

Here again I fail to reject my NULL Hypothesis in favor of Alternate Hypothesis.

Again data is in favor of NULL Hypothesis i.e. hotel rating is <=3

Here I am experiencing two different result just by changing my hypothesis. Please help me to understand why this is happening.Is there anything I am not taking correctly.

Note:- I have checked the normality condition using shapiro-wilk test and outlier using boxplot. All are fine.

[Why do statisticians say a non-significant result means “you can't reject the null” as opposed to accepting the null hypothesis?](http://stats.stackexchange.com/q/85903/17230). There's no contradiction in failing to have found much evidence either that the mean is less than 3 or that it's greater than 3; given that we know it's equal to 3 for your simulated data it shouldn't even be at all surprising. (BTW there's not much sense in testing data for normality when you know they come from a uniform distribution. But check your test again - it should be apparent with this sample size.) — Scortchi - Reinstate Monica, Jun 13 '16 at 10:51
@Scortchi thanks a lot. it is really helpful.But it will be more beneficial if you give me certain link of discussing similar approach. — learner, Jun 13 '16 at 11:41

Single Sample t-test Hypothesis Confusion

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