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Probability and Fair Coin Flips in Football Games

Explore the probabilities of coin flips and dice rolls in the context of football games. Understand the likelihood of different outcomes with detailed examples.

amcdermott
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Probability and Fair Coin Flips in Football Games

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  1. A “fair” coin is flipped at the start of a football game to determine which team receives the ball. The “probability” that the coin comes up HEADs is expressed as A.50/50“fifty-fifty” B.1/2 “one-half” C. 1:1 “one-to-one”

  2. A green and red die are rolled together. What is the probability of scoring an 11? A. 1/4 B. 1/6 C. 1/8 D. 1/12 E. 1/18 F. 1/36

  3. A coin is tossed twice in succession. The probability of observing two heads (HH) is expressed as A.1/2 B.1/4 C. 1D.0

  4. A coin is tossed twice in succession. The probability of observing two heads (HH) is expressed as A. 1/2 B. 1/4 C. 1 D. 0 It is equally likely to observe two heads (HH) as two tails (TT) T) True.F) False.

  5. A coin is tossed twice in succession. The probability of observing two heads (HH) is expressed as A. 1/2 B. 1/4 C. 1 D. 0 It is equally likely to observe two heads (HH) as two tails (TT) T) True.F) False. It is equally likely for the two outcomes to be identical as to be different. T) True.F) False.

  6. A coin is tossed twice in succession. The probability of observing two heads (HH) is expressed as A. 1/2 B. 1/4 C. 1 D. 0 It is equally likely to observe two heads (HH) as two tails (TT) T) True.F) False. It is equally likely for the two outcomes to be identical as to be different. T) True.F) False. The probability of at least one head is A. 1/2 B. 1/4 C. 3/4 D. 1/3

  7. Height in inches of sample of 100 male adults 61 64 67 70 70 71 75 72 72 69 68 70 65 67 62 59 62 66 66 68 68 73 71 72 73 71 71 68 69 68 69 65 63 70 70 76 71 72 74 60 56 74 75 79 72 72 69 68 68 68 62 66 66 66 61 77 75 74 63 72 63 62 65 65 66 65 67 67 65 67 68 62 67 60 68 65 70 70 69 70 68 73 64 71 71 68 70 69 73 72 70 69 67 64 67 58 66 69 76 73 Frequency table of the distribution of heights 56 1 57 0 58 1 59 1 60 2 61 2 62 5 63 3 64 3 65 7 66 7 67 8 68 12 69 8 70 10 71 7 72 8 73 5 74 3 75 3 76 2 77 1 78 0 79 1

  8. Number of classes K = 1 + 3.3 log10N = 1 + 3.3 log10100 = 1 + 3.3×2 = 7.6  8 Frequency table of the distribution of heights 56 1 57 0 2 58 1 59 1 60 2 5 61 2 62 5 63 3 11 64 3 65 7 66 7 22 67 8 68 12 69 8 30 70 10 71 7 72 8 20 73 5 74 3 75 3 8 76 2 77 1 78 0 2 79 1

  9. If events (the emission of an  particle from a uranium sample, or the passage of a cosmic ray through a scintillator) occur randomly in time, repeated measurements of the time between successive events should follow a “normal” (Gaussian or “bell-shaped”) curve T) True.F) False.

  10. If events occur randomly in time, the probability that the next event occurs in the very next second is as likely as it not occurring until 10 seconds from now. T) True.F) False.

  11. P(1)Probability of the first count occurring in in 1st second P(10)Probability of the first count occurring in in 10th second i.e., it won’t happen until the 10th second ??? P(1) = P(10) ??? = P(100) ??? = P(1000) ??? = P(10000) ???

  12. Imagine flipping a coin until you get a head. Is the probability of needing to flip just once the same as the probability of needing to flip 10 times? Probability of a head on your 1st try, P(1) = Probability of 1st head on your 2nd try, P(2) = Probability of 1st head on your 3rd try, P(3) =

  13. Probability of a head on your 1st try, P(1) =1/2 Probability of 1st head on your 2nd try, P(2) =1/4 Probability of 1st head on your 3rd try, P(3) =1/8 Probability of 1st head on your 10th try, P(10) =

  14. What is the total probability of ALL OCCURRENCES? P(1) + P(2) + P(3) + P(4) + P(5) + ••• =1/2+1/4 + 1/8 + 1/16 + 1/32 + ••• ?

  15. A six-sided die is rolled repeatedly until it gives a 6. What is the probability that one roll is enough?

  16. A six-sided die is rolled repeatedly until it gives a 6. What is the probability that one roll is enough? 1/6 What is the probability that it will take exactly 2 rolls?

  17. A six-sided die is rolled repeatedly until it gives a 6. What is the probability that one roll is enough? 1/6 What is the probability that it will take exactly 2 rolls? (probability of miss,1st try)(probability of hit)=

  18. A six-sided die is rolled repeatedly until it gives a 6. What is the probability that one roll is enough? 1/6 What is the probability that it will take exactly 2 rolls? (probability of miss, 1st try)(probability of hit)= What is the probability that exactly 3 rolls will be needed?

  19. The probability of a single COSMIC RAYpassing through a small area of a detector within a small interval of time Dt can be very small: p << 1 • cosmic rays arrive at a fairly stable, regular rate • when averaged over long periods • the rate is not constant nanosec by nanosec or • even second by second • this average, though, expresses the probability • per unit time of a cosmic ray’s passage • for example (even for a fairly large surface area) • 72000/min=1200/sec • =1.2/millisec = 0.0012/msec • =0.0000012/nsec

  20. The probability of a single COSMIC RAYpassing through a small area of a detector within a small interval of time Dt can be very small: p << 1 The probability of NOcosmic rays passing through that area during that interval Dtis A. pB. p2C. 2p D.( p - 1) E. ( 1 - p)

  21. The probability of a single COSMIC RAYpassing through a small area of a detector within a small interval of time Dt can be very small: p << 1 If the probability of one cosmic ray passing during a particular nanosec is P(1) = p << 1 the probability of 2 passing within the same nanosec must be A. pB. p2C. 2p D.( p - 1) E. ( 1 - p)

  22. The probability of a single COSMIC RAYpassing through a small area of a detector within a small interval of time Dtis p << 1 the probability that none pass in that period is ( 1 -p )1 While waiting N successive intervals (where the total time is t = NDt ) what is the probability that we observe exactly n events?

  23. The probability of a single COSMIC RAYpassing through a small area of a detector within a small interval of time Dtis p << 1 the probability that none pass in that period is ( 1 -p )1 While waiting N successive intervals (where the total time is t = NDt ) what is the probability that we observe exactlyn events? pn n “hits”

  24. The probability of a single COSMIC RAYpassing through a small area of a detector within a small interval of time Dtis p << 1 the probability that none pass in that period is ( 1 -p )1 While waiting N successive intervals (where the total time is t = NDt ) what is the probability that we observe exactlyn events? pn × ( 1 -p )??? n “hits” ??? “misses”

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