X = the number of freshmen selected from the study until one replied "yes" that same-sex couples should have the right to legal marital status.
X = the number of patients calling in claiming to have the flu, who actually have the flu.
X = 0, 1, 2, ...25
- X = number of questions answered correctly
- X ~ B
- We are interested in MORE THAN 75% of 32 questions correct. 75% of 32 is 24. We want to find P(x > 24). The event "more than 24" is the complement of "less than or equal to 24."
- P(x > 24) = 0
- The probability of getting more than 75% of the 32 questions correct when randomly guessing is very small and practically zero.
- X = the number of college and universities that offer online offerings.
- 0, 1, 2, …, 13
- X ~ B(13, 0.96)
- 12.48
- 0.0135
- P(x = 12) = 0.3186 P(x = 13) = 0.5882 More likely to get 13.
- X = the number of fencers who do not use the foil as their main weapon
- 0, 1, 2, 3,... 25
- X ~ B(25,0.40)
- 10
- 0.0442
- The probability that all 25 not use the foil is almost zero. Therefore, it would be very surprising.
- X = the number of matches
- 0, 1, 2, 3
- In dollars: −1, 1, 2, 3
- The answer is −0.0787. You lose about eight cents, on average, per game.
- The house has the advantage.
- X ~ B(15, 0.281)
-
- Mean = μ = np = 15(0.281) = 4.215
- Standard Deviation = σ = = = 1.7409
- P(x > 5)=1 – 0.7754 = 0.2246
P(x = 3) = 0.1927
P(x = 4) = 0.2259
It is more likely that four people are literate that three people are.
- X = the number of adults in America who are surveyed until one says he or she will watch the Super Bowl.
- X ~ G(0.40)
- 2.5
- 0.0187
- 0.2304
- X = the number of pages that advertise footwear
- X takes on the values 0, 1, 2, ..., 20
- X ~ B(20, )
- 3.02
- No
- 0.9997
- X = the number of pages we must survey until we find one that advertises footwear. X ~ G()
- 0.3881
- 6.6207 pages
- X ~ G(0.25)
-
- Mean = μ = = = 4
- Standard Deviation = σ = = ≈ 3.4641
- P(x = 10) = 0.0188
- P(x = 20) = 0.0011
- P(x ≤ 5) = 0.7627
- X ~ P(5.5); μ = 5.5; ≈ 2.3452
- P(x ≤ 6) ≈ 0.6860
- There is a 15.7% probability that the law staff will receive more calls than they can handle.
- P(x > 8) = 1 – P(x ≤ 8) ≈ 1 – 0.8944 = 0.1056
Let X = the number of defective bulbs in a string.
Using the Poisson distribution:
- μ = np = 100(0.03) = 3
- X ~ P(3)
- P(x ≤ 4) ≈ 0.8153
Using the binomial distribution:
- X ~ B(100, 0.03)
- P(x ≤ 4) = 0.8179
The Poisson approximation is very good—the difference between the probabilities is only 0.0026.
- X = the number of fortune cookies that have an extra fortune
- 0, 1, 2, 3,... 144
- 4.32
- 0.0124 or 0.0133
- 0.6300 or 0.6264
- As n gets larger, the probabilities get closer together.