• Skip to secondary menu
  • Skip to main content
  • Skip to primary sidebar
  • My Store
  • Glossary
  • Home
  • About Me
  • Contact Me

Statistics By Jim

Making statistics intuitive

  • Graphs
  • Basics
  • Hypothesis Testing
  • Regression
  • ANOVA
  • Probability
  • Time Series
  • Fun

Alternative hypothesis

By Jim Frost

The alternative hypothesis is one of two mutually exclusive hypotheses in a hypothesis test. The alternative hypothesis states that a population parameter does not equal a specified value. Typically, this value is the null hypothesis value associated with no effect, such as zero. If your sample contains sufficient evidence, you can reject the null hypothesis and favor the alternative hypothesis. The alternative hypothesis is often denoted as H1 or HA.

If you are performing a two-tailed hypothesis test, the alternative hypothesis states that the population parameter does not equal the null hypothesis value. For example, when the alternative hypothesis is HA: μ ≠ 0, the test can detect differences both greater than and less than the null value.

A one-tailed alternative hypothesis can test for a difference only in one direction. For example, HA: μ > 0 can only test for differences that are greater than zero.

Related

Related Articles:
  • How Hypothesis Tests Work: Significance Levels (Alpha) and P values
  • How to Identify the Distribution of Your Data
  • When Can I Use One-Tailed Hypothesis Tests?
  • Examples of Hypothesis Tests: Busting Myths about the Battle of the Sexes
  • Failing to Reject the Null Hypothesis

Primary Sidebar

Meet Jim

I’ll help you intuitively understand statistics by focusing on concepts and using plain English so you can concentrate on understanding your results.

Read More...

Buy My Introduction to Statistics eBook!

New! Buy My Hypothesis Testing eBook!

Buy My Regression eBook!

Subscribe by Email

Enter your email address to receive notifications of new posts by email.

    I won't send you spam. Unsubscribe at any time.

    Follow Me

    • FacebookFacebook
    • RSS FeedRSS Feed
    • TwitterTwitter
    • Popular
    • Latest
    Popular
    • How To Interpret R-squared in Regression Analysis
    • How to Interpret P-values and Coefficients in Regression Analysis
    • Measures of Central Tendency: Mean, Median, and Mode
    • Normal Distribution in Statistics
    • Multicollinearity in Regression Analysis: Problems, Detection, and Solutions
    • How to Interpret the F-test of Overall Significance in Regression Analysis
    • Understanding Interaction Effects in Statistics
    Latest
    • How to Find the P value: Process and Calculations
    • Sampling Methods: Different Types in Research
    • Beta Distribution: Uses, Parameters & Examples
    • Geometric Distribution: Uses, Calculator & Formula
    • What is Power in Statistics?
    • Conditional Distribution: Definition & Finding
    • Marginal Distribution: Definition & Finding

    Recent Comments

    • Hannah on How to Interpret Adjusted R-Squared and Predicted R-Squared in Regression Analysis
    • James on Introduction to Bootstrapping in Statistics with an Example
    • Jim Frost on Introduction to Bootstrapping in Statistics with an Example
    • Jim Frost on How To Interpret R-squared in Regression Analysis
    • Jim Frost on Comparing Regression Lines with Hypothesis Tests

    Copyright © 2022 · Jim Frost · Privacy Policy