Hypothesis Testing
ICSE · Class 12 · Artificial Intelligence
Quick revision notes for Hypothesis Testing — ICSE Class 12 Artificial Intelligence. Key concepts, formulas, and definitions for last-minute revision.
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Key Topics to Revise
1. Hypothesis and Hypothesis Testing
- A hypothesis is a testable, educated guess or a tentative explanation for a phenomenon that serves as the starting point for further investigation.
- Hypothesis testing is a statistical method used to determine whether there is enough evidence in a sample of data to infer that a certain condition is true for the entire population.
- Hypothesis testing always involves two opposing statements about a population.
2. Null Hypothesis and Alternative Hypothesis
- The null hypothesis represents the default assumption or status quo.
- The null hypothesis states that there is no effect, no relationship, or no difference between variables.
- The alternative hypothesis is the hypothesis being tested for.
3. Type I Error and Type II Error
- A Type I error is a false positive.
- A Type I error occurs when a true null hypothesis is rejected.
- The symbol for Type I error is α (alpha).
4. Correlation and Correlation Coefficient
- Correlation is the tendency of simultaneous variation between two variables.
- Correlation measures the degree to which two variables move in relation to each other.
- Positive correlation means that when one variable increases, the other also increases.
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