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Graph of number of coupons, n vs the expected number of trials (i.e., time) needed to collect them all, E (T ) In probability theory, the coupon collector's problem refers to mathematical analysis of "collect all coupons and win" contests.
The first equation shows that, after one second, an object will have fallen a distance of 1/2 × 9.8 × 1 2 = 4.9 m. After two seconds it will have fallen 1/2 × 9.8 × 2 2 = 19.6 m; and so on. The next-to-last equation becomes grossly inaccurate at great distances. If an object fell 10 000 m to Earth, then the results of both equations differ ...
Duration (finance) In finance, the duration of a financial asset that consists of fixed cash flows, such as a bond, is the weighted average of the times until those fixed cash flows are received. When the price of an asset is considered as a function of yield, duration also measures the price sensitivity to yield, the rate of change of price ...
Terminal velocity. The downward force of gravity ( Fg) equals the restraining force of drag ( Fd) plus the buoyancy. The net force on the object is zero, and the result is that the velocity of the object remains constant. Terminal velocity is the maximum speed attainable by an object as it falls through a fluid ( air is the most common example).
Weight distribution is the apportioning of weight within a vehicle, especially cars, airplanes, and trains. Typically, it is written in the form x / y, where x is the percentage of weight in the front, and y is the percentage in the back. In a vehicle which relies on gravity in some way, weight distribution directly affects a variety of vehicle ...
The mass of probability distribution is balanced at the expected value, here a Beta(α,β) distribution with expected value α/(α+β). In classical mechanics, the center of mass is an analogous concept to expectation. For example, suppose X is a discrete random variable with values x i and corresponding probabilities p i.
Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.
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