1. Dr. Amjad El-Shanti MD, PMH,Dr PH University of Palestine 2016
Test of significance
Dr. Amjad El-Shanti
MD, PMH,Dr PH
University of Palestine
2016

2. Test of Significance
Before getting into the step-by step procedure of a test of significance, you will find it helpful to look over the following definitions:
Hypothesis: A statement of belief used in the evaluation of population values.
Null Hypothesis: A claim there is no difference between the hypothesized values.
Alternative Hypothesis: A claim that disagree with the null hypothesis. If the null hypothesis is rejected, we are left with no choice but to fail to reject alternative hypothesis.

3. Test Statistics:
A statistic test used to determine the relative position of the hypothesized value from the mean of its distribution.
Pre-Post Study Paired T-Test
Two qualitative variables Chi-Square Test
Two quantitative Variables or more-----Correlation and linear regression
One quantitative and one qualitative T Test and ANOVA

4. Significant Level (α): P-Value:
The significant level is the magnitude of error that one is willing to take in making the decision to reject the null hypothesis.
P-Value:
The probability that the value of the calculated test statistics occurred by chance alone.
Type I and Type II Error:
Significance testing is method for assessing whether a result is likely to be due to chance or to some real effect.
It cannot prove that it is one or the other and one of two type of error may be occur in its use.
The null hypothesis may be rejected when it is in fact true (Type I Error) , or
Also we may fail to reject null hypothesis when it is false (Type II Error).
These are called Type I and Type II errors respectively.

5. Testing of hypotheses Type I and Type II Errors
No study is perfect,
there is always the chance for error
 - level of significance
1- - power of the test

6. Meaning of “Statistically Significant”
Research reports often state that the results were statistically significant (p-Value <0.05) or make some similar statements.
Such a comment means that the observed difference is too large to be explained by chance alone.
The significant level somewhat arbitrary selected at such values of α as 0.05, 0.025, 0.01, or is a measure of how significant a result is.
Statistically Significant means that the evidence obtained from the sample is not compatible with the null hypothesis.