The Poisson distribution is a discrete distribution. It is often used as a model for the number of events (such as the number of telephone calls at a business‚ number of customers in waiting lines‚ number of defects in a given surface area‚ airplane arrivals‚ or the number of accidents at an intersection) in a specific time period. It is also useful in ecological studies‚ e.g.‚ to model the number of prairie dogs found in a square mile of prairie. The major difference between Poisson and Binomial
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Written by: Afreen Baig http://economicpakistan.wordpress.com/2008/01/05/electricity/ "History" After the construction of the Hydro-Electric Tarbela Dam and the Mangla Dam‚ by General Ayub Khan and General Yahya Khan in the 1960’s‚ our governments failed to conceive and initiate major electricity projects. The inept governments of PML-N and PPP‚ that still consider themselves vital to democratic dialogue within the provinces‚ failed to create dialogue within provinces‚ on the most important
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Mathematics): Survival distributions Age-at-death random variable T0 – age-at-death (lifetime for newborn) random variable To completely determine the distribution of T0 ‚ we may use (for t ≥ 0)‚ (1) (cumulative) distribution function: F0 (t) = Pr(T0 ≤ t) (2) survival function: s0 (t) = 1 − F0 (t) = Pr(T0 > t) (3) probability density function: f0 (t) = F0 (t) = (4) force of mortality: µ0 (t) = d F0 (t) dt f0 (t) −s0 (t) = 1 − F0 (t) s0 (t) Requirements: (1) For distribution function‚
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expected average outcome over many observations.The common symbol for the mean (also known as the expected value of X) is ‚ formally defined by Variance - The variance of a discrete random variable X measures the spread‚ or variability‚ of the distribution‚ and is defined by The standard deviation is the square root of the variance. Expectation - The expected value (or mean) of X‚ where X is a discrete random variable‚ is a weighted average of the possible values that X can take‚ each value
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A population of measurements is approximately normally distributed with mean of 25 and a variance of 9. Find the probability that a measurement selected at random will be between 19 and 31. Solution: The values 19 and 31 must be transformed into the corresponding z values and then the area between the two z values found. Using the transformation formula from X to z (where µ = 25 and σ √9 = 3)‚ we have z19 = (19 – 25) / 3 = -2 and z31 = (31 - 25) / 3 = +2 From the area between z =±2 is 2(0
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‘Modelling and Forecasting Electricity Consumption of the Philippines’ Researcher: Alejon P. Padriganda Degree Program: Bachelor of Science in Applied Mathematics Adviser: Dennis A. Tarepe Ph.D Introduction Backgorund of the Study In the Philippines‚ electric power is becoming the main energy form relied upon in all economic sectors of the country. As time goes by‚ while different establishments and properties were built and developed‚ the demand for domestic electricity consumption within the
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My research is to determine if electricity moves better through thick wires or through thin wires. For this experiment I used two size D batteries‚ two flashlight bulbs‚ one 6.5 inch thin steel wool piece‚ one 6.5 inch thick steel wool piece‚ two 2 inch pieces of straw‚ and some electrical tape. Steel wool is a material made from thin fibers of steel made into a pad. (http://www.wisegeek.com/l-what-is-steel-wool.htm) There are many uses for steel wool. It can be used for sanding furniture‚ removing
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Normal Distribution It is important because of Central Limit Theorem (CTL)‚ the CTL said that Sum up a lot of i.i.d random variables the shape of the distribution will looks like Normal. Normal P.D.F Now we want to find c This integral has been proved that it cannot have close form solution. However‚ someone gives an idea that looks stupid but actually very brilliant by multiply two of them. reminds the function of circle which we can replace them to polar coordinate Thus Mean
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Probability distribution Definition with example: The total set of all the probabilities of a random variable to attain all the possible values. Let me give an example. We toss a coin 3 times and try to find what the probability of obtaining head is? Here the event of getting head is known as the random variable. Now what are the possible values of the random variable‚ i.e. what is the possible number of times that head might occur? It is 0 (head never occurs)‚ 1 (head occurs once out of 2 tosses)
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Electricity Essay – Its Shortage and Suggestions for overcoming it AATISH PALEKAR ARTICLES As a result of the drought in 1979‚ the Indian economy received a severe jolt. All of a sudden it was reported that there was acute power-famine. There was a wide gap between demand for electricity and its supply. Power cuts were imposed for long periods. To conserve electricity‚ market timings were changed from 8 A.M. to 7 P.M. Electricity was not supplied to consumers for several hours every day. Power-cuts
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