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Updated: Jun 27, 2025

Muscle Imbalances: Testing and Training Functional Eccentric Hamstring Strength in Athletic Populations
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Muscle Imbalances: Testing and Training Functional Eccentric Hamstring Strength in Athletic Populations

Published on: May 1, 2018

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体育科学从业人员的统计测试:识别个体运动员的表现收益

John R Harry1, Jacob Hurwitz2, Connor Agnew3

  • 1Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, Texas.

Journal of strength and conditioning research
|April 25, 2024
PubMed
概括

体育科学家可以使用模型统计和变化系数 (CV) 方法更好地检测运动员的改进. 这些方法为个人绩效增长提供了可靠的见解,避免了基于组的分析的局限性.

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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...
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Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test

In parametric statistics, two fundamental tests stand out for their utility and wide application: the Student's t-test and goodness-of-fit tests. These tests provide researchers with a robust method for drawing insights from data, testing hypotheses, and making informed decisions based on their findings.
The Student's t-test is a statistical test that examines if there is a statistically significant difference between the means of two groups. This test is instrumental when dealing with...
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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...
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Testing a Claim about Standard Deviation

A complete procedure to test a claim about population standard deviation or population variance is explained here.
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Comparing Experimental Results: Student's t-Test

The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...
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Bonferroni Test01:10

Bonferroni Test

The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
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