Hypothesis testing involves asserting a null hypothesis (H0) and alternative hypothesis (Ha) about a population based on a sample. Key steps include setting the hypotheses, choosing a significance level, selecting a test statistic like the chi-square or t-test, computing the test, and making a decision to reject or fail to reject the null hypothesis.

1. Testing Hypothesis

2. • A statistical hypothesis is an assertion or conjecture concerning one
or more populations.
• Important factors of Hypothesis Testing
• Population: The complete collection of all the elements to be studied.
Sample: A sub collection of elements drawn from a population.
• Hypothesis
1) Null (𝐻0)
2) Alternative (𝐻𝑎 or 𝐻1)
• Test (Statistics)
1) 𝜒2
test (Chi-square test)
2) t-student test or t-test
3) Fisher’s z-test

3. Procedure for testing the Hypothesis:
1) To set the hypothesis.
2) To set the suitable significant level.
3) To set the test criteria.
4) Computation.
5) Decision.

4. 1) To set the hypothesis.
a) Null (𝐻0)
b) Alternative (𝐻𝑎 or 𝐻1)
2) To set the suitable significant level.
Test the validity of 𝐻0 against 𝐻1 at certain level of significance, i.e. 5%
or 1%, etc.

10. 3) Test Statistic

11. 5) Decision