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Hypothesis Testing

A clear guide explaining hypothesis testing, its steps, and its role in research and analytics.

Written By: author avatar Tumisang Bogwasi
author avatar Tumisang Bogwasi
Tumisang Bogwasi, Founder & CEO of Brimco. 2X Award-Winning Entrepreneur. It all started with a popsicle stand.

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What is Hypothesis Testing?

Hypothesis testing is a statistical method used to make inferences about a population based on sample data. It helps determine whether there is enough evidence to support or reject a proposed assumption.

Definition

Hypothesis testing is the process of evaluating assumptions about population parameters using statistical techniques and sample data.

Key Takeaways

  • Used to test assumptions using data.
  • Involves null and alternative hypotheses.
  • Central to research, analytics, and decision-making.

Understanding Hypothesis Testing

The process begins with a null hypothesis (H₀), which represents the default assumption, and an alternative hypothesis (H₁), which represents the claim being tested. Statistical tests evaluate whether observed data is sufficiently unlikely under the null hypothesis.

Researchers calculate a test statistic and compare it to a critical value or use a p-value to decide whether to reject the null hypothesis. The choice of test depends on data type, distribution, and research design.

Hypothesis testing is widely used in economics, finance, medicine, marketing, and social sciences to support evidence-based decisions.

Real-World Example

A company tests whether a new marketing campaign increases average sales. The null hypothesis assumes no change, while the alternative hypothesis assumes higher sales after the campaign.

Importance in Business or Economics

Hypothesis testing is important because it:

  • Supports data-driven decision-making
  • Reduces reliance on intuition or bias
  • Validates research findings
  • Improves forecasting and strategy evaluation

Types or Variations

  • Z-Test — Used for large samples with known variance
  • T-Test — Used for smaller samples
  • Chi-Square Test — Tests relationships between categorical variables
  • ANOVA — Compares means across multiple groups
  • Null Hypothesis
  • P-Value
  • Statistical Significance

Sources and Further Reading

Quick Reference

  • Tests assumptions using sample data
  • Uses probability and statistics
  • Foundational in research and analytics

Frequently Asked Questions (FAQs)

What is a null hypothesis?

It is the default assumption that there is no effect or difference.

What does a p-value show?

The probability of observing results as extreme as the sample, assuming the null hypothesis is true.

Does rejecting H₀ prove H₁ is true?

It provides evidence in favor of H₁, but not absolute proof.

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Tumisang Bogwasi
Tumisang Bogwasi

Tumisang Bogwasi, Founder & CEO of Brimco. 2X Award-Winning Entrepreneur. It all started with a popsicle stand.