Hypothesis Testing And Decision Theory

Hypothesis Testing And Decision Theory

Hypothesis Testing and Decision Theory Null and Alternative Hypotheses Hypothesis Testing (Big Picture) Hypothesis testing is a method used in statistics to make decisions or inferences about a population based on sample data. You basically ask a question and then use data to decide whether the evidence supports an assumption or not. 1. Null Hypothesis (H₀) The null hypothesis is the default assumption —the idea that "nothing is happening" or "there is no effect or difference." It's what you're trying to test against . Example: Suppose a company claims their new battery lasts 10 hours. The null hypothesis would be: "The average battery life is 10 hours." 2. Alternative Hypothesis (H₁ or Ha) The alternative hypothesis is the opposite of the null —it's what you might believe is true if the data shows enough evidence . It represents a new effect, difference, or change. Using the battery example: The alternative might be "The average battery life is different from 10 hours" or "less than 10 hours" depending on what you are trying to test. Decision Theory Connection In decision theory, you’re essentially deciding between two actions: Reject the null hypothesis Fail to reject the null hypothesis Your decision depends on

Updated July 15, 2026