In statistical hypothesis testing you have a null hypothesis against which you are testing an alternative. The hypothesis concerns one or more characteristics of the distribution.
It is easier to illustrate the idea of directional and non-directional hypothesis. In studying the academic abilities of boys and girls the null hypothesis would be that boys and girls are equally able. One directional hypothesis would be that boys are more able. The non-directional alternative would be that there is a gender difference. You have no idea whether boys are more able or girls - only that they are not the same.
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A non-directional hypothesis only proposes a relationship. In contrast, a directional hypothesis also proposes a direction in the relationship. For example, when one variable increases, the other will decrease.
When the alternative hypothesis is non-directional, we use a two-tailed test. Example: H0: mean = 50 Ha : mean not equal to 50 Here is a directional hypothesis that would use a one-tailed test. H0: mean = 40 Ha : mean > 40 or H0: mean = 40 Ha: mean < 40
because Hypothesis itself is an assumption and we always use the term hypothesis only for assuming a perfect answer. so,we use mostly three forms,directional,non-directional and null hypothesis. it is a very simple and straightforward way to prove or make correct our hypothesis.
forming a hypothesis is when you come up with an educated guess.. what you think it may be . testing a hypothesis is when you're testing to see if someone else's guess is right.
examining/ experimenting/ testing/ verifying... it depends on the type of hypothesis to an extent I think.