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HomeHomework HelpstatisticsHypothesis Testing

Hypothesis Testing

A statistical procedure used to make inferences about a population based on a sample of data, involving the formulation of a hypothesis, selection of a test, computation of test statistics and p-values, and comparison to threshold values to draw conclusions about the presence of relationships or differences

intermediate
3 hours
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Overview

Hypothesis testing is a fundamental concept in statistics that allows researchers to make informed decisions based on sample data. By formulating null and alternative hypotheses, researchers can use statistical methods to determine whether there is sufficient evidence to support a claim. Understandi...

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Key Terms

Null Hypothesis
A statement that there is no effect or no difference, used as a starting point for testing.

Example: The null hypothesis states that a new drug has no effect on patients.

Alternative Hypothesis
The hypothesis that there is an effect or a difference, opposing the null hypothesis.

Example: The alternative hypothesis suggests that the new drug improves patient outcomes.

P-value
The probability of obtaining test results at least as extreme as the observed results, assuming the null hypothesis is true.

Example: A P-value of 0.03 indicates a 3% chance of observing the data if the null hypothesis is true.

Type I Error
The error made when rejecting a true null hypothesis.

Example: Concluding that a drug is effective when it actually is not.

Type II Error
The error made when failing to reject a false null hypothesis.

Example: Concluding that a drug is not effective when it actually is.

Significance Level
The threshold for determining whether a P-value indicates a statistically significant result.

Example: A significance level of 0.05 means results are significant if the P-value is less than 0.05.

Related Topics

Confidence Intervals
Understanding confidence intervals helps in estimating population parameters and their reliability.
intermediate
Regression Analysis
Regression analysis explores relationships between variables, often using hypothesis testing.
intermediate
ANOVA
Analysis of Variance (ANOVA) is used to compare means across multiple groups, involving hypothesis testing.
advanced

Key Concepts

Null HypothesisAlternative HypothesisP-valueType I and II Errors