The probability mass fünction öf the r.V.X is 1 f(x) = P(X3DX) 0.15 0.45 0.3 0.10 The P(X is at most 2) is O A. 0.6 O B. 1 OC.0.15 O D.0.9

Q: function Sx1.x,(#1, #z} = #, if 1<z; < 2 and 1 < x3 < 3' otherwise. fx,.x(1,2) = 10. What is the…

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Q: Let X be a random variable with the gamma probability density function. Derive the MSE of T=X2+2X

A: Gamma distribution: It is a continuous random variable, with the probability density function of…

Q: The joint probability mass function is given below: Y = 0 Y = 1 Y = 2 X = 0 X = 1 P(X|Y=2) = ? 1/6

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Q: Let X and Y be the number of tables and chairs in an office. p(x, y) of X and Y is given in the…

A: From the given information, the joint density for X and Y is,   y=0 y=1 y=2 y=3 x=1 0.05 0.06…

Continuous Probability Distributions

Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.

Normal Distribution

Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!