The maximum patent life for a drug is 17 years. Subtracting the length of time required by the FDAfor testing and approval of the drug provides the actual patent life for the drug that is, the lengthof time that the company has to recover research and development costs and to make a profit. Thedistribution of the lengths of actual patent lives for new drugs is given below, where Y is a randomvariable representing actual patent life of a drug (in years):yP(Y=y)F(y)4 5 6 7 8 9 10 110.06 0.08 0.11 0.15 0.22 0.18 0.12 0.08a) Complete the table above with the cumulative probability distribution for actual patent life(F(y) = P(Y ≤ y)).b) What is the probability that the actual patent life of a random drug is 6 years or less?c) What is the probability that the actual patent life of a random drug is more than 8 years? Showthis in two ways:i. using the probability distribution for Yii. using the cumulative probability distribution for Y, and applying our probability of comple-ments rule

Let Y be the random variable of the actual patent life of a drug (in years). The probability…

Answered: a) Complete the table above with the…

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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on average, 5.4 shoplifting incidents occur each week T EDGARS ELECTRONICS STORE. USING POISSON PROBABILITY DIRT. FORMULA, FIND THE PROB. THAT EXACTLY 3 SUCH INCIDENTS OCCUR DURING A GIVEN WEEK .
a. A random variable X has the following probability distribution: 0 x 18 5 x 18 10 x 18 15 x 18 20 x 18 25 x 18 P(X = x) 0.1 2m 0.2 0.1 0.04 0.07
he time it takes me to wash the dishes is uniformly distributed between 9 minutes and 18 minutes.What is the probability that washing dishes tonight will take me between 12 and 17 minutes?Give your answer accurate to two decimal places.
The joint probability distribution of precipitation X (inches) and runoff Y(cfs) (discretized here for simplicity) due to storms in the Lower Kaskaskia Valley is as follows: (a) What is the probability that the next storm will bring a precipitation of 2 or more inches and a runoff of more than 20 cfs? (b) After a storm, a precipitation of 2 inches is measured. What is the probability that the runoff in this storm is 20 cfs or more? (c) Are X and Y statistically dependent? Substantiate your answer. (d) Determine and plot the marginal PMF of runoff. (e) Determine the correlation coefficient between X and Y.
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please do this typewritten asap.
Aiyana has purchased the life insurance policy for her snake for the price of $100 per year and Aiyana will receive $5000 in case if her snake passes away. The insurance company estimated the probability of her snake passing away during the length of the policy to be 0.2%. Let XX be the insurance company's profit. Answer the following questions: 1. Create the probability distribution table for XX : XX outcome profit xx ,$ P(X=x)P(X=x) snake passes away snake survives 2. Use the probability distribution table to find the following: E[X]=μX=E[X]=μX= dollars. (Round the answer to 1 decimal place.) SD[X]=σX=SD[X]=σX= dollars. (Round the answer to 1 decimal place.)
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Two fair dice are rolled. Find the joint probability distribution of Y1 and Y2, where Y1 is the larger of the values obtained on the dice and Y2 is the absolute value of the difference of the values obtained on the dice. Find the marginal probability distributions of Y1 and Y2 from the joint probability distribution.
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As you walk into your econometrics exam, a friend bets you $10 that she will outscore you on the exam. Let ✗ be a random variable denoting your winnings. X can take the values 10, if you win teh bet, 0 if there is a score tie, or -10 if you lose. You know that the probability distribution for ✗ is denoted by f(x) and it depends on whether she studied for the exam or not. Let Y be the random variable that indicates if she studied, Y = 0 if she studied and Y = 1 if she did not study. The following table denotes the joint distribution of X and Y : Y=0 Y=1 f(x) X = -10 0.18 P1 P2 X = 0 0 P3 0.3 X = 10 P4 0.45 P5 f(y) P6 0.75 Probabilities P1, P2, P3, P4, P5, P6 are not displayed in the table. Answer the following items: (a) (b) (a) Compute the Probabilities P1, P2, P3, P4, P5, P6 of the table. (b) Compute the expectation E(X). Should you take the bet? (c) What is the probability distribution of your winnings if you know that she did not study, namely, P(X = −10|Y = 1), P(X = 0|Y = 1), P(X…

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