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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.
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JordanIn statistical hypothesis testing, the null hypothesis is usually that there is no difference between some parameter derived from two experiments (or samples). The alternative can either be that there is a difference but you do not specify beforehand whether that difference is positive or negative. Such a hypothesis is non-directional.
However, you may have reason to use the alternative that the parameter from one set is bigger than the other. That is a directional hypothesis.
For example, imagine you are studying gender differences in exam results and you consider the average marks in a Geography test. The null hypothesis would normally be that the two means are the same. The non-directional alternative would be that there is a difference between boys and girls but you don't know who will do better. One directional hypothesis would be that the boys' mean score is higher.
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What is the directional and non-directional hypothesis testing?
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.
Why you write hypothesis in different forms?
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.
Examples of non-directional hypothesis?
Boys and girls are different heights. As opposed to: Boys are taller than girls.
When to apply two tailed test in testing hypothesis?
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
How do you determine directional or non-directional alternate hypotheses?
Whether you frame your alternative hypothesis, Ha, as one-sided (directional) or two-sided (non-directional) is really up to you, but should be decided before you look at the data. It will affect the calculation of your p-value and ultimately your conclusions from the test. In most cases there will be a sound, obvious reason for choosing one or the other.For example, if you were testing the effectiveness of a new anti-cholesterol drug you'd probably only be interested in testing whether the average of the experimental group was lower than the control group. So Ha is directional, or one sided. If on the other hand you were testing, for example, whether a Group A performed better on a test than Group B, your Ha would be that the average of Group A does not equal Group B. That is, you're not sure, before you run the test, whether Group A should perform better or worse than Group B. So your test is non-directional, or two-sided.
