Related Experiment Video
Updated: Aug 19, 2026

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools
Published on: June 20, 2020
Determination of the physical working capacity in children using three different regression models
Abstract:
Experimental findings of the working capacity at a heart rate of 170 bts/min (W170) were compared to predicted values. Statistical tests were applied to examine the suitability and the error of prediction of three different regression models: a linear regression line, a polynomial regression model, and a "break point" regression model, which were compared to the time course of the heart rate during a linearly increasing work load from 0 to 100 W during 10 min. For this study the results of 28 children, 15 and 16 years old, and students of physical education were investigated. When a linear regression line was compared to these data, systematic deviations between measured data and the values estimated by this model were found. When the W170 was predicted using this model from the data collected during the first 10 min of an exercise procedure for the determination of the heart rate index, the physical working capacity was overestimated. The polynomial regression model and the "break point" regression model agreed with the time course of the heart rate without systematic error and allowed an unbiased prediction of the W170 from the first 10 min of the exercise test.
Related Concept Videos
Regression Toward the Mean
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Rate of Change: Problem Solving

