A hypothesis is a prediction, which one expects to occur and
intends to test in a research study (Aron, Aron, & Coups, 2009). Hypothesis
testing is a process using statistics to determining if the results of a study support
a certain theory, which one believes applies to a certain population (Aron,
Aron, & Coups, 2009). Hypothesis testing is a process that involves five
steps:

Step 1: Restate the question as a research
hypothesis and a null hypothesis about the populations.

In this first
step one makes a research hypothesis concerning a predicted relation among populations.
The null and research hypothesizes are the opposite of each other. A correct research
hypothesis means the null hypothesis cannot be correct, and a correct null
hypothesis means the research hypothesis cannot be correct.

Step 2: Determine the characteristics of the comparison distribution.

In the second step by reaching a true null hypothesis the population
situation represents the comparison distribution, which is the distribution
compared to the score and based on the results of the sample.

Step 3: Determine the cutoff sample score on the comparison distribution
at which the null hypothesis should be rejected.

In this third step, reject
the null hypothesis if the point of the cutoff sample score reaches or exceeds the
sample score. If the null hypothesis is true the Z score is set at a score, which
would be unlikely.

Step 4: Determine your sample’s score
on the comparison distribution.

In this fourth step one gathers the
test’s sample results.

Step 5: Decide whether to reject
the null hypothesis.

In this fifth step one either declares the test
invalid or rejects the null hypothesis by comparing the cut off Z score to the
sample’s Z score.

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