The weather on any given day in a particular city can be sunny, cloudy, or rainy. It has been observed to bepredictable largely on the basis of the weather on the previous day. Specfically:if it is sunny on one day, it will be sunny the next day 3/10 of the time, and be cloudy the next day 1/5 of thetime●if it is cloudy on one day, it will be sunny the next day 2/5 of the time, and be cloudy the next day 2/5 of thetime• if it is rainy on one day, it will be sunny the next day 3/10 of the time, and be cloudy the next day 1/5 of thetimeUsing 'sunny', 'cloudy', and 'rainy' (in that order) as the states in a system, set up the transition matrix for aMarkov chain to describe this system.Use your matrix to determine the probability that it will rain on Tuesday if it is sunny on Sunday.0P=000000Probability of rain on Tuesday = 0

Given that the weather on any given day in a particular city can be sunny, cloudy, or rainy. It has…

Answered: The weather on any given day in a…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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1.) Let arr86 be a binary variable equal to 1 if a man was arrested during 1986, and zerootherwise. You have a dataset of young men from California who were born in 1960 or1961 and have at least one arrest prior to 1986. You also have data on the proportion ofprior arrests that led to a conviction (pcnv), the average sentence served from priorconvictions in months (avgsen), months spent in prison since age 18 prior to 1986(tottime), months spent in prison in 1986 (ptime86), and the number of quarters (0 to 4)that the man was legally employed in 1986 (qemp86). You estimate the following linearprobability model (standard errors are in parentheses): arr86 = 0.441 - .162pcnv + .0061avgsen - .0023tottime (.017) (.021) (.0065) (.005) - .022ptime86 - .043qemp86 (.005) (.005) n= 2725R2=.0474 a) Interpret the coefficient on avgsen, commenting on both magnitude and significance. Based on these results, do longer sentences deter future crime?…
The weather on any given day in a particular city can be sunny, cloudy, or rainy. It has been observed to be predictable largely on the basis of the weather on the previous day. Specfically: ● • if it is sunny on one day, it will be sunny the next day 3/10 of the time, and be cloudy the next day 1/5 of the time • if it is cloudy on one day, it will be sunny the next day 1/2 of the time, and be cloudy the next day 1/10 of the time ● if it is rainy on one day, it will be sunny the next day 7/10 of the time, and be cloudy the next day 1/5 of the time Using 'sunny', 'cloudy', and 'rainy' (in that order) as the states in a system, set up the transition matrix for a Markov chain to describe this system. Use your matrix to determine the probability that it will rain on Wednesday if it is sunny on Sunday. 000 P=000 000 Probability of rain on Wednesday = 0
3
Only do question 52 for Statistics and probability I
Suppose that A E Mmxn(R) is a matrix of user ratings of various movies (on a scale of 1 to 5). Suppose we have computed the SVD of А, and decided to keep the 10 largest singular values as the most important determining factors for a user's choice of movie. Suppose also that a new user has joined the movie subscription service, and has rated some, but not all, of the movies. To predict how this new user will rate other movies (and thus, to determine which ones to recommend), all movies the user has not watched are assigned the average rating for that movie given by all users to form a new matrix A' E M(m+1)xn(R), and the rank-10 approximation of A' is computed from its SVD. The values in the approximation to A' are taken as the predicted ratings for the new user. Given this procedure, which of the following conclusions is most correct?
2.T.3 A car rental agency has three locations, A, B, and C, and a complete fleet of 1000 cars. Most people return their car to the same location they rented it from: this happens .9 of the time, to be precise. Of the people renting at location A, .01 of them return the car to location B, and .09 to location C. Of the people renting at location B, .01 of them return the car to location A, and .09 to location C. Of the people renting at location C, .01 of them return the car to location B, and .09 to location A. This car agency has been in operation for many years, so one expects their cars to be distributed according to the steady state solution. How many cars will there be in location A?
just need final answer
on solution 3 the probablity that tails would appear on both coins is 14?
I need assistance with parts D, and E
2 James is born on September 1, On September 6, four years after he is born, he will begin JK. His mother wants to check his biorhythms for the day he will begin JK a) What is the intellectual y-value for the day that James will begin JK? b) What type of day, intellectually, will the first day of JK be for James? c) Based on all three cycles in the theory of biorhythms, what type of day will the first day of JK be for James?
11. Given P(A) = 0.25, P(B) = 0.28, and P(B|A) = 0.28, are A and B independent or dependent?

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