Hypothesis testing is a statistical method used to make inferences or conclusions about a population based on sample data. It involves formulating a null hypothesis and an alternative hypothesis, collecting data, and determining the likelihood of obtaining the observed results if the null hypothesis were true.
Imagine you're trying to find out if a new study app improves test scores. You could create two groups: one that uses the app (experimental group) and another that doesn't (control group). By comparing their test scores, you can determine if the app has a significant impact.
Null Hypothesis: A statement that assumes there is no significant difference or relationship between variables.
Alternative Hypothesis: A statement that suggests there is a significant difference or relationship between variables.
Type I Error: When we reject the null hypothesis but it is actually true.
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