Can absolute and proportional anthropometric characteristics distinguish stronger and weaker powerlifters?

Justin W L Keogh1, Patria A Hume, Simon N Pearson

  • 1Institute of Sport and Recreation Research New Zealand, School of Sport and Recreation, AUT University, Auckland, New Zealand. justin.keogh@aut.ac.nz

Related Concept Videos

Exercise and Muscle Performance01:27

Exercise and Muscle Performance

Exercise induces a range of adaptations in muscle tissue, depending on the type and duration of activity. Such physical training can be broadly categorized into two types: endurance exercises and resistance exercises.
Endurance exercises
Endurance exercises involve running, swimming, or cycling, which require repetitive movements with low force output. When a person engages in endurance exercise, a few noticeable changes occur in their skeletal muscles. For instance, the number of capillaries...
Power01:08

Power

The concept of work involves force and displacement; meanwhile, the work-energy theorem relates the net work done on a body to the difference in its kinetic energy, calculated between two points on its trajectory. While none of these quantities or relations involves time explicitly, we know that the time available to accomplish work is often just as important as the amount of work itself. For example, sprinters in a race may have achieved the same velocity at the finish, therefore,...
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
Coefficient of Correlation01:12

Coefficient of Correlation

The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the strength of the linear...