An assumption about the population parameter.
Ex: I assume the mean SBP of participants is 120 mmHg.
Types of Hypothesis:
There are two types of Hypothesis.
1. Null Hypothesis.
2. Alternative Hypothesis.
Null Hypothesis: [Ho]
A neutral statement about population parameter is known as Null Hypothesis.
It is denoted by Ho.
Null Hypothesis [Ho]: There is no significance difference in height of Male & Female.
Alternative Hypothesis [H1]:
The opposite or complimentary statement of Null Hypothesis is known as Alternative Hypothesis.
It is denoted by H1.
Alternative Hypothesis [H1]: There is significance difference in height of male & female.
Steps for Hypothesis Testing:
Step I: Formulate Hypotheses:
Define both the null hypothesis (H₀) and the alternative hypothesis (H₁).
Step II: Identify Data
Identify which type of data and level of measurement is given.
Step III: Determine appropriate statistical test.
Conduct an appropriate statistical test (such as a t-test, chi-square test, or ANOVA) to analyze the data.
Step IV:
Calculate p-value and decide whether to reject or Accept the null hypothesis.
Compare the p-value from the test with the significance level (α). If the p-value is less than α, reject the null hypothesis in favor of the alternative hypothesis.
Step V: Interpret Results
Based on the decision, conclude whether there is sufficient evidence to support the alternative hypothesis or if the null hypothesis remains plausible.
