* First step, prepare the alternative and null hypotheses.

* Second step, test the null hypothesis, this is done by carrying out a statistical test of significance to determine whether it can be rejected, and consequently, whether there is a difference between the groups under investigation

* Third step, the sample statistics appropriate for the sample, variables and hypothesis are calculated

* Fourth step, determine if the null hypothesis can be rejected by conducting a significance test

* Fifth step, the decision is made to reject or fail to reject the null hypothesis

Comparing the means of two or more groups

The function of comparing the means of two or more groups is used to determine the probability of an event given two distinctively independent sample data sets with equal variances. This concept ties directly into forming and ultimately testing a hypothesis when two sample sets of data are to be used in order to prove the null hypothesis. The distance from the hypothesis to the mean has value in that the value of the distance itself shows a corresponding value to the probability of occurrence. Testing the means of two or more groups can be achieved with an analysis of variance.

Calculating the correlation between two variables

Calculating the correlation between two variables is described as, the change in one variable will create a corresponding change in the other variable. It tells you whether variables are positively or inversely related, and the degree to which the variables tend to move together. Two variables that contribute to a common cause are suggested to be a high correlation between the two variables. A change in one is responsible for a change in the other. Pearson’s r-value is used to quantify the correlation between two discrete variables.

For me I have struggled understand the correct way to actually word a hypothesis. You have to make sure it is...