Null and Alternative Hypotheses

Statistics · Axiom Academy

LESSON Null and Alternative Hypotheses Understanding the foundation of hypothesis testing: formulating claims about population parameters The null hypothesis is the default claim or status quo assumption. It typically represents "no effect," "no difference," or "no change." We assume the null hypothesis is true unless we have strong evidence against it. Always contains an equality (=, ≤, or ≥) Represents the skeptical position What we assume to be true initially The hypothesis we test against 2. The Alternative Hypothesis (H₁ or Hₐ) The alternative hypothesis is what the researcher is trying to prove or find evidence for. It represents a departure from the status quo—a change, difference, or effect. Represents the research claim or question What we need evidence to support Accepted only with sufficient proof 3. Two-Sided vs One-Sided Tests The form of your alternative hypothesis determines whether you conduct a two-sided or one-sided test. 4. Writing Hypotheses for Different Scenarios Let's practice formulating hypotheses for various real-world situations. The key is identifying the parameter of interest and the claim being tested. Understanding null and alternative hypotheses is the foundation of hypothesis testing. Here are the essential takeaways: Complementary: H₀ and H₁ must be mutually exclusive and exhaustive—together they cover all possibilities Equality: The null hypothesis always contains the equality component

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