The central limit theorem is one of two fundamental theories of probability. It's very important because its the reason a great number of statistical procedures work. The theorem states the distribution of an average has the tendency to be normal, even when it turns out that the distribution from which the average is calculated is definitely non-normal.
The Central Limit Theorem (CLT) is a theorem that describes the fact that if a number of samples are taken from a population, the distribution of the means of the samples will be normal. This is true for all different distributions, whether or not the population is normal or something else. The main exception to this is that the theorem does not work particularly well if the samples are small (
Pythagoras theorem will always work with a right-angled triangle.
no
Yes, the work-kinetic energy theorem holds for both positive and negative work. Positive work increases the kinetic energy of an object, while negative work decreases it. The theorem states that the net work done on an object is equal to the change in its kinetic energy.
If the work done on an object is equal to the object's change in kinetic energy, then the object is in a state of work-energy theorem. This theorem states that the work done on an object is equal to the change in its kinetic energy.
work
No it never works.
The work-energy theorem states that the work done on an object is equal to the change in its kinetic energy. This theorem is important because it allows us to analyze and predict the motion of objects by considering the work done on them. It provides a powerful tool for understanding and solving problems in mechanics.
You don't, unless you work in engineering. The Wikipedia article on "binomial theorem" has a section on "Applications".
The work-energy theorem states that the work done on an object is equal to the change in its kinetic energy. This means that if work is done on an object, it will either speed up or slow down depending on the direction of the work.
Brahmagupta worked with Pythogoras.