Probability and Random Variables - Prof. Debra Wood, Assignments of Mathematics

Various probability concepts including discrete, finite, and continuous random variables, probability mass functions (p.m.f.), probability density functions (p.d.f.), and cumulative distribution functions (c.d.f.). It includes examples and practice problems related to binomial, poisson, and exponential distributions, as well as verifying if given functions are p.d.f.s.

Typology: Assignments

Pre 2010

Uploaded on 08/31/2009

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WS 25 – Random Variable Name:
#
(For questions 1-11) Show work and explanations on a separate piece of paper and/ or make
appropriate spacing. (12 -15 can be written in appropriate spaces.) If you can’t briefly answer the
question this implies that you do not fully understand the vocabulary and/or symbols in this section. Go
back and review, so you can discuss this material. Make sure you show all steps and use correct
translation and function notation. Attach this sheet to the top of your work
Some of this work should or can be done in excel, if you use excel attach you excel work.
1. [Hint: use excel ] ]The personnel director of a large company has several similar positions to fill. It
is estimated that there is a 55% chance that an applicant will accept a job offer that the company
makes. Suppose that all of those receiving offers make independent decisions about whether or not to
accept. Thus, the number, A, of acceptances received from n offers is a binomial random variable.
a) If 15 job offers are made, and A is the number of acceptances received from 15 offers, find the
distribution of A (this means find all possible values of A and their corresponding probabilities.
Write the f
A
(a) and F
A
(a))
b) Graph the p.m.f. of A and the c.d.f. of A. (you should do this in excel)
Attach your excel worksheet.
c) What is the probability that 6 offers will be accepted?
d) What is the probability that at least 6 offers are accepted?
2. According to a Tobacco Research and Intervention Program, only 7% of the nation’s cigarette
smokers ever enter into a treatment program to help them quit smoking. In a random sample of 25
smokers, let X be the number of smokers who enter into a treatment program.
(Write values if need to 6 decimal places or in correct scientific notation) - (attach your excel work)
a. How many smokers from this sample do you expect to enter a treatment program?
(Hint: What is the distribution of X ?)
b. Write the pdf and cdf for this distribution (hint you can use excel)
c. What is the probability that 6 smokers from the random sample will enter into a treatment program?
d. What is the probability that at most 3 smokers from the random sample will enter into the treatment
program?
e. What is the probability that at least 7 smokers from the random sample will enter into the treatment
program?
f. What is the probability that more than 2 smoker from the random sample will enter into the treatment
program?
g. What is the probability that at least 2 smoker from the random sample will enter into the treatment
program?
3. Alfred E. Neuman has three pennies, four nickels, two dimes, and one quarter in his pocket. Let X be
the denomination of a coin selected at random from his pocket.
Example: P(X=5) = 4/10 The probability that a randomly picked coin is a nickel is 40%
P(X 5) =7/10 The probability that a randomly picked coin has value of a nickel or less is 70%
a) Construct a table of the p.m.f.
b) Graph the p.m.f. (either by hand or excel your choice)
c) Construct a table representing the c.d.f.
d) Write the c.d.f. as a piecewise function
e) Graph the c.d.f. (either by hand or excel your choice)
f) Find
( 10)
P X
=
g) Find
( 25)
P X
h) Find
( 10)
P X
i) Find
( 10)
P X
<
j) Find
( )
E X
pf3
pf4
pf5

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WS 25 – Random Variable Name:

( For questions 1-11 ) Show work and explanations on a separate piece of paper and/ or make appropriate spacing. (12 -15 can be written in appropriate spaces.) If you can’t briefly answer the question this implies that you do not fully understand the vocabulary and/or symbols in this section. Go back and review, so you can discuss this material. Make sure you show all steps and use correct translation and function notation. Attach this sheet to the top of your work Some of this work should or can be done in excel, if you use excel attach you excel work.

  1. [Hint: use excel ] ]The personnel director of a large company has several similar positions to fill. It is estimated that there is a 55% chance that an applicant will accept a job offer that the company makes. Suppose that all of those receiving offers make independent decisions about whether or not to accept. Thus, the number, A , of acceptances received from n offers is a binomial random variable. a) If 15 job offers are made, and A is the number of acceptances received from 15 offers, find the distribution of A (this means find all possible values of A and their corresponding probabilities. Write the fA ( a ) and FA ( a )) b) Graph the p.m.f. of A and the c.d.f. of A. (you should do this in excel) Attach your excel worksheet. c) What is the probability that 6 offers will be accepted? d) What is the probability that at least 6 offers are accepted?
  2. According to a Tobacco Research and Intervention Program, only 7% of the nation’s cigarette smokers ever enter into a treatment program to help them quit smoking. In a random sample of 25 smokers, let X be the number of smokers who enter into a treatment program.

(Write values if need to 6 decimal places or in correct scientific notation) - (attach your excel work) a. How many smokers from this sample do you expect to enter a treatment program? (Hint: What is the distribution of X ?) b. Write the pdf and cdf for this distribution (hint you can use excel) c. What is the probability that 6 smokers from the random sample will enter into a treatment program? d. What is the probability that at most 3 smokers from the random sample will enter into the treatment program? e. What is the probability that at least 7 smokers from the random sample will enter into the treatment program? f. What is the probability that more than 2 smoker from the random sample will enter into the treatment program? g. What is the probability that at least 2 smoker from the random sample will enter into the treatment program?

  1. Alfred E. Neuman has three pennies, four nickels, two dimes, and one quarter in his pocket. Let X be the denomination of a coin selected at random from his pocket. Example: P( X =5) = 4/10 The probability that a randomly picked coin is a nickel is 40% P( X ≤ 5) =7/10 The probability that a randomly picked coin has value of a nickel or less is 70% a) Construct a table of the p.m.f. b) Graph the p.m.f. (either by hand or excel your choice) c) Construct a table representing the c.d.f. d) Write the c.d.f. as a piecewise function e) Graph the c.d.f. (either by hand or excel your choice) f) Find (^) P X ( =10) g) Find P X ( ≤25) h) Find P X ( ≤10) i) Find P X ( <10) j) Find E X ( )
  1. The probability that an acute patient recovers for the SARS virus is 95%. There are 3 patients in ICU recovering from this virus. Let X record the number of patients that survive. What is the probability that only 2 survive (rounded to 2 decimal places if needed)?
  2. The cable guy will be arriving at John’s home between 10am – 3pm and that any time within this interval is likely to be his arrival time. Let X be the random variable that is his arrival time. a) Construct a p.d.f. and c.d.f ( write the function ) b) What is the probability that the cable guy comes at 2:07:35? c) What is the probability that the cable guy comes between 11:45am and 1:05pm? Find this answer using two different methods (one is using the pdf and the other is cdf)
  3. Suppose that customers arrive at the checkout counter at a grocery store. Let X be the continuous random variable that gives the time, in minutes and parts of minutes, between the arrivals of consecutive customers. It can be shown that this is an exponential random variable and that the average time between customers is 42 seconds. Give exact value and if needed round to 4 decimal places.

a. Change the mean between the arrivals of consecutive customers into minutes. ( mean and time must be in the same units – all calculations must be done in minutes ) b. Write the fX ( x ) and FX ( x ) c. What is the probability that the between arrival time is 42 seconds ( change to minutes )? d. What is the probability that consecutive customers inter-arrival time is less than 1.25 minutes? e. What is the probability that consecutive customers’ inter-arrival time is at least 1 minute? f. What is the probability that consecutive customer’s inter-arrival time is between 30 seconds and 1 minute? ( remember to change seconds to minutes-note on the test you will not be reminded )

  1. Let T be the random variable giving the lifetime, in hours, of the graphics card in your computer. The manufacturer claims that T has an exponential distribution with parameter α = 5000 hours. ( i ) What is the probability that your card fails less than 3,000 hours? ( ii ) What is the probability that your card lasts for at least 5,000 hours? ( iii ) What is the probability that your card lasts for exactly 5,000 hours? (Think carefully about this!)
  2. Decide if the following function could represent a p.m.f. , a p.d.f. a c.d.f., or none of these. Give a reason for your answer.

x 0 1 2 3

f ( x ) 0.1 0.1 0.3 0.

  1. Given an example for each of the following types of random variable. Your example must not be from a lecture, class, class notes, worksheets, or text.

a. An example of a discrete random variable b. An example of a finite random variable c. An example of a continuous random variable:

  1. Write a paragraph describing the abbreviations written below. Include what they mean, differences between them, when and how they would be used. It may be helpful to include examples. p.m.f. c.d.f. p.d.f.
  1. For each of the following, decide which could be a p.m.f. (Probability mass function), a p.d.f. (Probability density function), a c.d.f. (Cumulative distribution function), or none of these. If the answer is none, explain why. You may place your answers on the graphs below a.

x y x x

b.

c. d.

e. f.

x x y x

x

  1. Which of these graphs are a pmf and which are pdf?

a b c d

the length on the x-axis is 5

  1. Is this a uniform finite random variable function? Explain

0

0

0

  1. 05

  2. 15

  3. 25

Proabability Mass Function

0

1 2 3 4 5 6 7 8 9 x