Null & Alternative hypotheses

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NEET PG High-Yield: Hypothesis Testing

Hypothesis testing is the cornerstone of inferential statistics. It provides a formal framework for making decisions about populations based on sample data.

Core Definitions

Hypothesis Description
Null (H_0) States there is no difference or no effect. We start by assuming this is true.
Alternative (H_A) States there is a significant difference or effect (what we aim to prove).
High-Yield NEET PG Pearls:

  • Type I Error (\alpha): Rejecting the null hypothesis when it is actually true (False Positive).
  • Type II Error (\beta): Failing to reject the null hypothesis when it is actually false (False Negative).
  • Power of a Study (1 - \beta): The probability of correctly rejecting the null hypothesis when the alternative is true.
  • P-value: The probability of obtaining the observed results (or more extreme) assuming the null hypothesis is true. If p < 0.05, we reject the null hypothesis.