# Thread: Which tests do I have to use in order to test my hypotheses?

1. ## Re: Which tests do I have to use in order to test my hypotheses?

Pearson's correlation basically measures the strength of the correlation between two factors. In this case, I'm assuming these two factors in Pearson's correlation are employee's performance rating and the status of the relation, correct? If so, then the correlation between the given performance rating and the status of the relation is positive. Unless, of course, you're talking about significance which is a different ball game.

3. ## Re: Which tests do I have to use in order to test my hypotheses?

Just to be sure, what is the value of Pearson's correlation?

5. ## Re: Which tests do I have to use in order to test my hypotheses?

Correct! So the correlation between employee's performance rating and the status of the relation is positive.

If you perform a t-test and the p-value is 0,532, then you accept the null hypothesis. But is the p-value is 0.001 then you should accept H1.
When you accept H1, I would say yes there the relation positively effects the performance rating, because there is a positive correlation between employee's performance rating and the status of the relation.

Or am I wrong?

6. ## Re: Which tests do I have to use in order to test my hypotheses?

This is just the correlation of women.

I have splitted my sample into man and women and perform the tests seperatly.

And the correlation is negative.

7. ## Re: Which tests do I have to use in order to test my hypotheses?

Correct! So the correlation between employee's performance rating and the status of the relation is positive.
Right!

If you perform a t-test and the p-value is 0,532, then you accept the null hypothesis. But is the p-value is 0.001 then you should accept H1.
When you accept H1, I would say yes there the relation positively effects the performance rating, because there is a positive correlation between employee's performance rating and the status of the relation.

Or am I wrong?
A p-value of 0.001 is very good statistical evidence for H1 since it has a probability of extreme or more extreme of 1,000 to 1, so you can safely reject the null-hypothesis.

As for the conclusion, you can say there is a relationship if your independent t-test is statistically significant; however, it is important to know that the relationship may not be practically significant as you think. This is one problem with t-tests. They don't tell you how strong the relationship is, only evidence. You can, however, use Pearson's correlation to determine how strong is the effect. You can also calculate the effect-size as well, but that may be too advance for you.

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Musibrique (11-02-2012)