Moving college health research forward: Reconsidering our reliance on statistical significance testing

Adam E Barry1, Danny Valdez2, Patricia Goodson3

  • 1a Department of Health and Kinesiology , Texas A&M University , College Station , Texas , USA.

Related Concept Videos

Statistical Significance01:50

Statistical Significance

Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
22.1K
Significance Testing: Overview01:04

Significance Testing: Overview

Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
12.7K
Statistical Hypothesis Testing01:16

Statistical Hypothesis Testing

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.
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...
7.0K
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
491
Significance of Center of Mass01:12

Significance of Center of Mass

The center of mass of an object is defined as the mass-weighted average position of all the particles that comprise the object. The significance of the center of mass of an object can be seen by looking at its dynamics. The time derivative of the center of mass gives its velocity, assuming that the object's mass remains constant over time. Furthermore, the total linear momentum of an object can be seen as the linear momentum of a single particle of the object's total mass moving with...
7.7K
Cholesterol: Significance and Regulation01:29

Cholesterol: Significance and Regulation

Although not a source of energy, cholesterol plays a significant role as a foundational structure for bile salts, steroid hormones, and vitamin D, as well as being a crucial component of plasma membranes. Approximately 15% of blood cholesterol is derived from our diet, with the remainder synthesized from acetyl CoA by the liver and intestines. Cholesterol is eliminated from the body through its conversion into bile salts, which are eventually discarded in the feces.
Considering cholesterol and...
1.4K