What Hypothesis Testing Meaning, Applications & Example
Statistical method for validating assumptions about data.
What is Hypothesis Testing?
Hypothesis Testing is a statistical method used to make inferences or draw conclusions about a population based on sample data. It involves formulating a null hypothesis (H0) and an alternative hypothesis (H1), then determining whether the sample data supports or rejects the null hypothesis.
Types of Hypothesis Tests
- Z-test: Used when the sample size is large and the population variance is known.
- T-test: Used when the sample size is small and the population variance is unknown.
- Chi-square test: Used to determine whether there is a significant association between categorical variables.
Applications of Hypothesis Testing
- A/B Testing: Used to compare two versions of a webpage or app to determine which performs better.
- Drug Testing: Helps determine whether a new drug is effective compared to a placebo.
- Quality Control: Assesses whether a manufacturing process produces products that meet certain specifications.
Example of Hypothesis Testing
In a clinical trial testing the effectiveness of a new medication, the null hypothesis might state that the medication has no effect on patients, while the alternative hypothesis could state that the medication has a positive effect. By analyzing the trial data, researchers can determine if the evidence supports rejecting the null hypothesis and accepting the alternative.