1. Suppose Nancy E Gillies has classes five days a week. She attends classes five days aweek 80% of the time, 4 days of the week 10% of the time, three days of the week1/30 of the time, never goes exactly two days in a week, one day 1/30 of the time,and no days 1/30 of the time. Suppose one week is randomly selected.D. Compute both μ, o for this Probability Density FunctionE. If Class was 30 weeks long how many days did Nancy not attend classes?

Answered: Image /qna-images/answer/941796ea-b210-474a-80d5-a18e5628c86f.jpg

Answered: 1. Suppose Nancy E Gillies has classes…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Suppose that a random variable X has the following probability density function. SC(36-x²) 0 ≤ x ≤ 6 otherwise f(x) = {C (² Find the expected value of X. (You will need to find the value of the constant C so that f is a pdf.)
This problem involves drawing three cards from a deck of cards. Assume that the deck contains 3 aces, 5 other face cards, and 15 non-face cards and that you randomly draw 3 cards. A random variable Z is defined to be 5 times the number of aces plus 4 times the number of other face cards drawn. 1. How many different values are possible for the random variable Z? 2. Fill in the table below to complete the probability density function. Be certain to list the values of Z in ascending order.
(6) An otherwise fair sir sided die has been tampered with in an attempt to cheat at a dice game. The effect is that the 1 and 6 faces have a different probability of occurring than the 2, 3, 4 and 5 faces. Let ở be the probability of obtaining a 1 on this biased die. Then the outcomes of rolling the biased die have the following probability mass function. Table 1 The p.m.f. of outcomes of rolls of a biased die Outcome 1 2 3 4 5 6 Probability 0 (1- 20) (1 – 20) (1– 20) {(1 – 20) 0 Heeessary (ii) The value of 0 is unknown. Data from which to estimate the value of 0 were obtained by rolling the biased die 1000 times. The result of this experiment is shown in Table 2. Table 2 Outcomes of 1000 independent rolls of a biased die Outcome 1 3 4 5 6. Frequency 205 154 141 165 145 190 Show that the likelihood of 0 based on these data is L(0) = C0395 (1 – 20)605, where C is a positive constant, not dependent on 0. (iii) Show that Stare what rule is ased, L'(0) = C 6394 (1 – 20)®04 (395 – 2000 6).…
Show work for every step. Two types of customers (Preferred and Regular) call a service center. Preferred customers call with rate 3 per hour, and Regular customers call with rate 5 per hour. The interarrival times of the calls for each customer type are exponentially distributed. If the call center opens at 8:00 AM, what is the probability that the first call (regardless of customers type who calls) is received before 8:15 AM?
A shop receives a shipment of 1000 lamps. The probability that any individual lamp is defective is 0.2%. Assume the defectiveness is independent of cach lamp. Let X be the number of defective lamps in the batch of 1000. What is the probability mass function of X? O P(X = k) = (00) 0.002* (1 – 0.002)1000 , k = 0,1, 2, ..., 1000 O P(X = k) = 0.002* (1 – 0.002)1000–&, k = 0, 1, 2, .….., 1000 O P(X = k) = (1000) 0.002* (1 – 0.002)1000 , k = 1, 2, ..., 1000 O P(X = k) = (00)0.002100- (1 – 0.002)*, k = 0, 1, 2, ..., 1000
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