Hypothesis Testing (with Future Work)
Hypothesis testing is a formal procedure of testing your ideas about the world using statistics.
Null hypothesis (\(H_0\)) and Alternate hypothesis (\(H_1\))
Low within group variance & high between group variance : low p-value
Does independent variable affect dependent variable?
- Null hypothesis : Independent variable does not affect dependent variable.
- Alternative hypothesis : Independent variable affects dependent variable.
The significance level, or alpha (α), is a value that the researcher sets in advance as the threshold for statistical significance. It is the maximum risk of making a false positive conclusion (Type I error) that you are willing to accept.
APA guidelines advise reporting not only p values but also effect sizes and confidence intervals wherever possible to show the real world implications of a research outcome.
In statistics, a Type I error is a false positive conclusion, while a Type II error is a false negative conclusion.
References
Hypothesis Testing | A Step-by-Step Guide with Easy Examples
Statistical Significance in A/B testing (Calculation and the Math Behind it)
A/B-Test Calculator - Power & Significance - ABTestGuide.com
Next
What is Effect Size and Why Does It Matter? (Examples)
Understanding Confidence Intervals | Easy Examples & Formulas