2. In probability, it is common to model the deviation of a day's temperature from the monthlyaverage temperature using the Gaussian probability density function,1f(t) =%3DeThis means that the probability that the day's temperature will be between t = a and t = bdifferent from the monthly average temperature is given by the area under the graph ofy = f(t) between t = a and t = b.A related function is2F(2) =e-t /9 dt, x >0.x > 0.This function gives the probability that the day's temperature is between t = -x and t = xdifferent from the monthly average temperature. For example, F(1) 2 0.36 indicates thatthere's roughly a 36% chance that the day's temperature will be within 1 degree (between 1degree less and 1 degree more) of the monthly average.1(a) Find a power series representation of F(x) (write down the power series using sigmanotation).(b) Use your answer to (a) to find a series equal to the probability that the day's temperaturewill be within 2 degrees of the monthly average.(c) Now approximate your answer to (b) to within 0.001 of the actual value. Make sure youjustify that the error in your approximation is no greater than 0.001.

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Answered: 2. In probability, it is common to…

A First Course in Probability (10th Edition)

10th Edition

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Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

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Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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TF.12 The joint pdf of the lifetimes X and Y in years of two batteries working in parallel is (see picture) a) Find the probability P(Y ≤ 0.5). b) Find the expected values E(X) and E(XY).
Let T represent the lifetime in years of a part which follows a Weibull distribution with shape 2 and scale 5. (a) What is E(T )? Make sure to simplify the gamma function in terms of pi.(b) What is V(T )? Make sure to simplify the gamma function in terms of pi.
(b) The probability density of a function is given by p(x) from x = 1 to x = 4. That is 62 x3 dx = 1 62 P(x) dx = - 00 Determine the value of the standard deviation.
A probability density curve is described by 2 line segments. The first connects (0, 1/7) and (3.5. 1/7), and the other connects (3.5, 1/7) to the x-axis. Part A: Sketch the probability density curve as described. (Be sure to label all values) Part B: Determine the x-value where the second segment crosses the x-axis. Part C: Determine P(X 0.05). Part E: Determine the median x-value of this distribution.
The exponential distribution is a probability distribution for non-negative real numbers. It is often used to model waiting or survival times. The version that we will look at has a probability density function of the form p(y|v) = exp(-e¯ºy — v) (1) where y R+, i.e., y can take on the values of non-negative real numbers. In this form it has one parameter: a log-scale parameter v. If a random variable follows an exponential distribution with log-scale v we say that Y~ Exp(v). If Y~ Exp(v), then E [Y] =e" and V [Y] = e²v. 1. Produce a plot of the exponential probability density function (1) for the values y E (0, 10), for v = 1, v = 0.5 and v= 2. Ensure the graph is readable, the axis are labeled appropriately and a legend is included. ta il 2. Imagine we are given a sample of n observations y = (y₁,..., yn). Write down the joint proba- bility of this sample of data, under the assumption that it came from an exponential distribution with log-scale parameter v (i.e., write down the…
Suppose that the interval between eruptions of a particular geyser can be modelled by an exponential distribution with an unknown parameter 0 > 0. The probability density function of this distribution is given by f(x; 0) = 0e 0¹, x > 0. The four most recent intervals between eruptions (in minutes) are x₁ = 32, x₂ = 10, x3 = 28, x4 = 60; their values are to be treated as a random sample from the exponential distribution. (a) Show that the likelihood of based on these data is given by L(0) 04-1306 = (b) Show that L'(0) is of the form L'(0) = 0³ e 1300 (4- 1300). (c) Show that the maximum likelihood estimate of 0 based on the data is ~ 0.0308 making your argument clear. (d) Explain in detail how the maximum likelihood estimate of that you have just obtained in part (c) relates to the maximum likelihood estimator of for an exponential distribution.
d. Denote the expected return and its standard deviation as functions of π byμ(π ) and σ (π ). The pair (μ(π ), σ (π )) trace out a curve in the plane as πvaries from 0 to 1. Plot this curve. I need to draw a graph from this??
Q1. Suppose X is a continuous random variable. Find an example of a probability density function for X giving expected value E(X) = 1 and variance V (X) = 3 if X has . . . (a.) a uniform distribution. (b.) an exponential distribution. (c.) a normal distribution. In each case, if there is no such probability density function, explain why this is so.
3. The level of impurity (in percent) in the product of a certain chemical process is a random variable with probability density function 3 64 -x²(4 - x) 0 0 < x < 4 otherwise a. What is the probability that the impurity level is greater than 3%? b. What is the probability that the impurity level is between 2% and 3%? c. Find the mean impurity level. d. Find the variance of the impurity levels.
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