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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.
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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.
(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?
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 )
a. An example of a discrete random variable b. An example of a finite random variable c. An example of a continuous random variable:
x y x x
b.
c. d.
e. f.
x x y x
x
a b c d
the length on the x-axis is 5
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0
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05
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25
Proabability Mass Function
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1 2 3 4 5 6 7 8 9 x