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The corpulence index yields valid results even for very short and very tall persons, [7] which is a problem with BMI — for example, an ideal body weight for a person 152.4 cm tall (48 kg) will render BMI of 20.7 and CI of 13.6, while for a person 200 cm tall (99 kg), the BMI will be 24.8, very close to the "overweight" threshold of 25, while ...
One-repetition maximum (one-rep max or 1RM) in weight training is the maximum amount of weight that a person can possibly lift for one repetition. It may also be considered as the maximum amount of force that can be generated in one maximal contraction. [1]
According to this setup, a male athlete weighing 320 pounds and lifting a total of 1400 pounds would have a normalised lift weight of 353.0, and a lifter weighing 200 pounds and lifting a total of 1000 pounds (the sum of their highest successful attempts at the squat, bench, and deadlift) would have a normalised lift weight of 288.4. Thus the ...
Rates of obesity worldwide tripled from 1975 to 2016 to involve some 1.8 billion people and 39% of the world adult population. [ 3 ] A commonly asserted "rule" (the Wishnofsky Rule, aka Wishnofsky's Rule) for weight gain or loss, is based on the research of Max Wishnofsky (December 17, 1899 – August 2, 1965), a Russian-born physician who had ...
The Harris–Benedict equation (also called the Harris-Benedict principle) is a method used to estimate an individual's basal metabolic rate (BMR).. The estimated BMR value may be multiplied by a number that corresponds to the individual's activity level; the resulting number is the approximate daily kilocalorie intake to maintain current body weight.
In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...
The rate of reinforcement for fixed-ratio schedules is easy to calculate, as reinforcement rate is directly proportional to response rate and inversely proportional to ratio requirement (Killeen, 1994). The schedule feedback function is therefore: =.
As can be estimated from weight loss and the density , the wear coefficient can also be expressed as: [2] K = 3 H W P L ρ {\displaystyle K={\frac {3HW}{PL\rho }}} As the standard method uses the total volume loss and the total sliding distance, there is a need to define the net steady-state wear coefficient: