Statistical hypothesis testing  Wikipedia
Fail to reject the null hypothesis with either a one tailed or a two tailed from PSYCH 2000 at Fordham
One and twotailed tests  Wikipedia
You should decide whether to use the onetailed or twotailed probability before you collect your data, of course. A onetailed probability is more powerful, in the sense of having a lower chance of false negatives, but you should only use a onetailed probability if you really, truly have a firm prediction about which direction of deviation you would consider interesting. In the chicken example, you might be tempted to use a onetailed probability, because you're only looking for treatments that decrease the proportion of worthless male chickens. But if you accidentally found a treatment that produced 87% male chickens, would you really publish the result as "The treatment did not cause a significant decrease in the proportion of male chickens"? I hope not. You'd realize that this unexpected result, even though it wasn't what you and your farmer friends wanted, would be very interesting to other people; by leading to discoveries about the fundamental biology of sexdetermination in chickens, in might even help you produce more female chickens someday. Any time a deviation in either direction would be interesting, you should use the twotailed probability. In addition, people are skeptical of onetailed probabilities, especially if a onetailed probability is significant and a twotailed probability would not be significant (as in our chocolateeating chicken example). Unless you provide a very convincing explanation, people may think you decided to use the onetailed probability after you saw that the twotailed probability wasn't quite significant, which would be cheating. It may be easier to always use twotailed probabilities. For this handbook, I will always use twotailed probabilities, unless I make it very clear that only one direction of deviation from the null hypothesis would be interesting.
In the second experiment, you are going to put human volunteers with high blood pressure on a strict lowsalt diet and see how much their blood pressure goes down. Everyone will be confined to a hospital for a month and fed either a normal diet, or the same foods with half as much salt. For this experiment, you wouldn't be very interested in the P value, as based on prior research in animals and humans, you are already quite certain that reducing salt intake will lower blood pressure; you're pretty sure that the null hypothesis that "Salt intake has no effect on blood pressure" is false. Instead, you are very interested to know how much the blood pressure goes down. Reducing salt intake in half is a big deal, and if it only reduces blood pressure by 1 mm Hg, the tiny gain in life expectancy wouldn't be worth a lifetime of bland food and obsessive labelreading. If it reduces blood pressure by 20 mm with a confidence interval of ±5 mm, it might be worth it. So you should estimate the effect size (the difference in blood pressure between the diets) and the confidence interval on the difference.
CORRELATION  Missouri State University
This criticism only applies to twotailed tests, where the null hypothesis is "Things are exactly the same" and the alternative is "Things are different." Presumably these critics think it would be okay to do a onetailed test with a null hypothesis like "Foot length of male chickens is the same as, or less than, that of females," because the null hypothesis that male chickens have smaller feet than females could be true. So if you're worried about this issue, you could think of a twotailed test, where the null hypothesis is that things are the same, as shorthand for doing two onetailed tests. A significant rejection of the null hypothesis in a twotailed test would then be the equivalent of rejecting one of the two onetailed null hypotheses.
Social Research Methods  Knowledge Base  Correlation
Hypothesis Testing  Six Sigma Material

One Sample TTest  Statistics Solutions
Summary

16/01/2018 · Hypotheses
Hypothesis Testing Steps

Hypothesis Testing Binomial Distribution  Real …
Define the Problem; State the Objectives; Establish the Hypothesis (lefttailed, righttailed, or two tailed test)