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Statistical Hypothesis Testing

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Hypothesis testing is a critical statistical procedure facilitating informed, evidence-based decisions. It begins with a hypothesis, which is a tentative explanation, or a prediction about a population parameter. This hypothesis can be either a null hypothesis (H0), indicating no effect or difference, or an alternative hypothesis (Ha), suggesting an effect or difference.
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Related Experiment Video

Updated: May 15, 2026

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Published on: March 7, 2019

The ActivityStat hypothesis: the concept, the evidence and the methodologies.

Sjaan R Gomersall¹, Alex V Rowlands, Coralie English

¹Health and Use of Time (HUT) Group, Sansom Institute for Health Research, University of South Australia, Adelaide, SA, Australia. sjaan.gomersall@mymail.unisa.edu.au

Sports Medicine (Auckland, N.Z.)

|January 19, 2013

Summary

The ActivityStat hypothesis suggests compensatory changes in physical activity, but experimental evidence remains inconclusive. Further research is needed to understand energy expenditure regulation and activity compensation across diverse populations.

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Area of Science:

Exercise Physiology
Behavioral Science
Public Health

Background:

The ActivityStat hypothesis posits that changes in physical activity in one area lead to compensatory changes in another to maintain stable energy expenditure.
Existing research predominantly relies on observational studies, creating a need for experimental investigation.

Purpose of the Study:

To provide a conceptual clarification of the ActivityStat hypothesis.
To systematically review experimental research that either supports or refutes the concept of compensation in physical activity or energy expenditure.

Main Methods:

A systematic review of electronic databases was performed to identify experimental studies on the ActivityStat hypothesis.
Studies were critically appraised using a tool designed to assess conceptual considerations of the hypothesis.

Main Results:

Twenty-eight studies spanning 26 years, employing diverse methodologies and participant demographics (children to elderly), were included.
Fifteen studies indicated evidence of compensation, while 13 did not, with subgroup analyses yielding mixed findings across various factors.

Conclusions:

A significant body of experimental evidence on compensation exists but has been largely overlooked in the ActivityStat debate.
Current experimental evidence is inconclusive, lacking a unified approach to the ActivityStat question, necessitating refined future research designs.