Chapter 9 Discrete Mathematics

Size: px
Start display at page:

Download "Chapter 9 Discrete Mathematics"

Transcription

1 Section 9. Basic Combinatorics 355 Chapter 9 Discrete Mathematics Section 9. Basic Combinatorics Exploration. Six: ABC, ACB, BAC, BCA, CAB, CBA.. Approximately person out of 6, which would mean 0 people out of No. If they all looked the same, we would expect approximately 0 people to get the order right simply by chance. The fact that this did not happen leads us to reject the look-alike conclusion. 4. It is likely that the salesman rigged the test to mislead the office workers. He might have put the copy from the more expensive machine on high-quality bond paper to make it look more like an original, or he might have put a tiny ink smudge on the original to make it look like a copy. You can offer your own alternate scenarios. Quick Review Section 9. Exercises. There are three possibilities for who stands on the left, and then two remaining possibilities for who stands in the middle, and then one remaining possibility for who stands on the right: 3 # # 6.. Any of the four jobs could be ranked most important, and then any of the remaining three jobs could be ranked second, and so on: 4 # 3 # # Any of the five books could be placed on the left, and then any of the four remaining books could be placed next to it, and so on: 5 # 4 # 3 # # Any of the five dogs could be awarded st place, and then any of the remaining four dogs could be awarded nd place, and so on: 5 # 4 # 3 # # There are 3 # 4 possible pairs: K Q, K Q, K Q 3, K Q 4, K Q, K Q, K Q 3, K Q 4, K 3 Q, K 3 Q, K 3 Q 3, and K 3 Q There are 3 # 4 possible routes. In the tree diagram, B represents the first road from town A to town B, etc. 7. 9!36,880 (ALGORITHM) There are letters, where S and I each appear 4 times and P appears times. The number of distinguishable permutations is! 4!4!! 34, There are letters, where A appears 3 times and O and T each appear times. The number of distinguishable permutations is! 3!!!,663,00.. The number of ways to fill 3 distinguishable offices from a pool of 3 candidates is 3P 3 3! 0! 76.. The number of ways to select and prioritize 6 out of projects is P 6! 665,80. 6! 3. 4 # 3 # # # # # # A 6! 6 -! 6 # 5 # 4! 30 4! 9! 9 -! 9 # 8 # 7! 7 7! 0! 7!0-7! 0 # 9 # 8 # 7! 7! # 3 # # 0 0! 3!0-3! 0 # 9 # 8 # 7! 3! # 0 # 9 # 8 7! 3 # # 0 9. combinations 0. permutations. combinations. permutations (different roles) 3. There are 0 choices for the first character, 9 for the second, 6 for the third, then 5, then 8, then 7, then 6: 0 # 9 # 6 # 5 # 8 # 7 # 6 9,656, There are 36 choices for each character: ,466, There are 6 possibilities for the red die, and 6 for the green die: 6 # There are possibilities for each flip: B B B 3 C C C 3 C 4 C C C 3 C 4 C C C 3 C 4

2 356 Chapter 9 Discrete Mathematics C 3 5C 5 48C Choose 7 positions from the 0: 0! 0C 7 7!0-7! 0! 7!3! 77,50 3. Choose A and K, and cards from the other 50: C # 50 C # 50! 50 C!50 -! 50!!39! 37,353,738, C We either have 3,, or student(s) nominated: 6C 3 6 C 6 C We either have 3,, or appetizer(s) represented: 5C 3 5 C 5 C Each of the 5 dice have 6 possible outcomes: ! 36. 0C 8 8!0-8! 0! 5, 970 8!! *4*3* Since each topping can be included or left off, the total number of possibilities with n toppings is n. Since 048 is less than 4000 but 4096 is greater than 4000, Luigi offers at least toppings. 40. There are n subsets, of which n - are proper subsets ,765, True. 5! 3!5-3! 5! 3!! 300 5! 5!5-5! 5! 5!47!,598,960 48! 3!48-3! 48! 3!45! 7,96 8! 3!8-3! 8! 3!5! 56 a n a b a!n - a! a!b! n - b!b! a n b b 44. False. For example, a 5 is greater than a 5 b 0 4 b There are a 6 different combinations of vegetables. The total number of entreé-vegetable-dessert b 5 variations is 4 # 5 # The answer is D P 5 30,40. The answer is D. 47. np n The answer is B. n - n! 48. There are as many ways to vote as there are subsets of a set with 5 members. That is, there are 5 ways to fill out the ballot. The answer is C. 49. Answers will vary. Here are some possible answers: (a) Number of 3-card hands that can be dealt from a deck of 5 cards (b) Number of ways to choose 3 chocolates from a box of chocolates (c) Number of ways to choose a starting soccer team from a roster of 5 players (where position matters) (d) Number of 5-digit numbers that can be formed using only the digits and (e) Number of possible pizzas that can be ordered at a place that offers 3 different sizes and up to 0 different toppings. 50. Counting the number of ways to choose the eggs you are going to have for breakfast is equivalent to counting the number of ways to choose the ten eggs you are not going to have for breakfast. 5. (a) Twelve (b) Every 0 represents a factor of 0, or a factor of 5 multiplied by a factor of. In the product 50 # 49 # 48 #... # #, the factors 5, 0, 5, 0, 30, 35, 40, and 45 each contain 5 as a factor once, and 5 and 50 each contain 5 twice, for a total of twelve occurrences. Since there are 47 factors of to pair up with the twelve factors of 5, 0 is a factor of 50! twelve times. 5. (a) Each combination of the n vertices taken at a time determines a segment that is either an edge or a diagonal. There are n C such combinations. (b) Subtracting the n edges from the answers in (a), we find that nc - n!n -! - n nn - n - 3n - n. 53. In the nth week, 5 n copies of the letter are sent. In the last week of the year, that s 5 5.*0 36 copies of the letter. This exceeds the population of the world, which is about 6*0 9, so someone (several people, actually) has had to receive a second copy of the letter. 54. Six. No matter where the first person sits, there are the 3!6 ways to sit the others in different positions relative to the first person. 55. Three. This is equivalent to the round table problem (Exercise 4), except that the necklace can be turned upside-down. Thus, each different necklace accounts for two of the six different orderings. 56. The chart on the left is more reasonable. Each pair of actresses will require about the same amount of time to interview. If we make a chart showing n (the number of actresses) and n C (the number of pairings), we can see that chart allows approximately 3 minutes per pair throughout, while chart allows less and less time per pair as n gets larger. Number Number of Time per Pair Time per Pair n pairs n C Chart Chart

3 Section 9. The Binomial Theorem There are 5 C 3 635,03,559,600 distinct bridge hands. Every day has 60 # 60 # 4 86,400 seconds; a year has days, which is 3,556,736 seconds. Therefore it will 635,03,559,600 take about L 0,3 years. (Using 365 days 3,556,736 per year, the computation gives about 0,36 years.) 58. Each team can choose 5 players in C 5 79 ways, so there are 79 67,64 ways total. Section 9. The Binomial Theorem Exploration. 3C 0 3! 0!3!, 3C 3!!! 3, 3C 3! These are (in order) the!! 3, 3C 3 3! 3!0!. coefficients in the expansion of (ab) 3.. { }. These are (in order) the coefficients in the expansion of (ab) { }. These are (in order) the coefficients in the expansion of (ab) 5. Quick Review 9.. x xyy. a abb 3. 5x -0xyy 4. a -6ab9b 5. 9s st4t 6. 9p -4pq6q 7. u 3 3u v3uv v 3 8. b 3-3b c3bc -c x 3-36x y54xy -7y m 3 44m n08mn 7n 3 4. a 0 9 b x y 9 a 0 0 b x0 y 0 x 0 0x 9 y 45x 8 y 0x 7 y 3 0x 6 y 4 5x 5 y 5 0x 4 y 6 0x 3 y 7 45x y 8 0xy 9 y 0 5. Use the entries in row 3 as coefficients: (xy) 3 x 3 3x y3xy y 3 6. Use the entries in row 5 as coefficients: (xy) 5 x 5 5x 4 y0x 3 y 0x y 3 5xy 4 y 5 7. Use the entries in row 8 as coefficients: (pq) 8 p 8 8p 7 q8p 6 q 56p 5 q 3 70p 4 q 4 56p 3 q 5 8p q 6 8pq 7 q 8 8. Use the entries in row 9 as coefficients: (pq) 9 p 9 9p 8 q36p 7 q 84p 6 q 3 6p 5 q 4 6p 4 q 5 84p 3 q 6 36p q 7 9pq 8 q x y 0 a 0 0 b x0 y 0 a 0 b x9 y a 0 b x8 y a 9 b 9!!7! 9 # 8 # 36 a 5 b 5!!4! 5 # 4 # 3 # 4 # 3 # # 365 a b 66! 66!0! a 66 0 b 66! 0!66! a 0 3 b x7 y 3 a 0 4 b x6 y 4 a 0 5 b x5 y 5 a 0 6 b x4 y 6 a 0 7 b x3 y 7 a 0 8 b x y 8 Section 9. Exercises a b 4 a 4 0 b a4 b 0 a 4 b a3 b a 4 b a b a 4 3 b a b 3 a 4 4 b a0 b 4 a 4 4a 3 b 6a b 4ab 3 b 4 a b 6 a 6 0 b a6 b 0 a 6 b a5 b a 6 b a4 b a 6 3 a3 b 3 a 6 4 b a b 4 a 6 5 b a b 5 a 6 6 b a0 b 6 a 6 6a 5 b 5a 4 b 0a 3 b 3 5a b 4 6ab 5 b 6 3. x y 7 a 7 0 b x7 y 0 a 7 b x6 y a 7 b x5 y a 7 3 b x4 y 3 a 7 4 b x3 y 4 a 7 5 b x y 5 a 7 6 b x y 6 a 7 7 b x0 y 7 x 7 7x 6 y x 5 y 35x 4 y 3 35x 3 y 4 x y 5 7xy 6 y , , f(x)(x-) 5 x 5 5x 4 ( )0x 3 ( ) 0x ( ) 3 5x( ) 4 ( ) 5 x 5-0x 4 40x 3-80x 80x-3 8. g(x)(x3) 6 x 6 6x # 5 3 5x 4 # 3 5x # 3 4 6x # 0x # x 6 8x 5 35x 4 540x 3 5x 458x h(x)(x-) 7 (x) 7 7(x) 6 ( )(x) 5 ( ) 35(x) 4 ( ) 3 35(x) 3 ( ) 4 (x) ( ) 5 7(x)( ) 6 ( ) 7 8x 7-448x 6 67x 5-560x 4 80x 3-84x 4x-

4 358 Chapter 9 Discrete Mathematics 0. f(x)(3x4) 5 (3x) 5 5(3x) 4 # 4 03x 3 # 4 0(3x) # x # x 5 60x 4 430x x 3840x 04. (xy) 4 (x) 4 4(x) 3 y6(x) y 4(x)y 3 y 4 6x 4 3x 3 y4x y 8xy 3 y 4. (y-3x) 5 (y) 5 5(y) 4 ( 3x)0(y) 3 ( 3x) 0(y) ( 3x) 3 5(y)( 3x) 4 ( 3x) 5 3y 5-40y 4 x70y 3 x -080y x 3 80yx 4-43x x - y 6 x 6 6 x 5 - y 5 x 4 # - y 0 x 3 - y 3 5 x - y 4 6 x-y 5 - y 6 x 3-6x 5/ y / 5x y-0x 3/ y 3/ 5xy -6x / y 5/ y 3 x 3 4 x 4 4 x x # 3 4 x (x 3) 5 (x ) 5 5(x ) 4 x -0 5x -8 90x 6 70x 4 405x (a-b 3 ) 7 a 7 7a 6 ( b 3 )a 5 ( b 3 ) 35a 4 ( b 3 ) 3 35a 3 ( b 3 ) 4 a ( b 3 ) 5 7a( b 3 ) 6 ( b 3 ) 7 a 7-7a 6 b 3 a 5 b 6-35a 4 b 9 35a 3 b -a b 5 7ab 8 -b 7. Answers will vary. 8. Answers will vary. 9. a n b!n -! n n -!! n -!3n - n - 4! a n n - b 30. a n r b r!n - r! n - r!r! n - r!3n - n - r4! a n n - r b 3. n - r - n - r n -! r -!3n - - r - 4! n -! r!n - - r! rn -! rr -!n - r! n -!n - r r!n - rn - r -! rn -! n - rn -! r!n - r! r!n - r! r n - rn -! r!n - r! r!n - r! n r x 4x3x 8x 3x 9 # 3 0x 0x - # - 3 # x - # (a) Any pair (n, m) of nonnegative integers except for (, ) provides a counterexample. For example, n and m3: (3)!5!0, but!3!68. (b) Any pair (n, m) of nonnegative integers except for (0, 0) or any pair (, m) or (n, ) provides a counterexample. For example, n and m3: # 3! 6! 70, but,! # 3! # a n b a n b n n - n n - nn - n n n - n n n n! n -!3n - n - 4! n - n n n n 35. True. The signs of the coefficients are determined by the powers of the ( y) terms, which alternate between odd and even. 36. True. In fact, the sum of every row is a power of. 37. The fifth term of the expansion is n!!n -!!n -! n -!3n - n - 4! n! n -!! n -!! nn - n n a 8 The answer is C. 4 bx4 4 0x 4. n 38. The two smallest numbers in row 0 are and 0. The answer is B. 39. The sum of the coefficients of (3x-y) 0 is the same as the value of (3x-y) 0 when x and y. The answer is A. 40. The even-numbered terms in the two expressions are opposite-signed and cancel out, while the odd-numbered terms are identical and add together. The answer is D. 4. (a), 3, 6, 0, 5,, 8, 36, 45, 55. (b) They appear diagonally down the triangle, starting with either of the s in row. (c) Since n and n represent the sides of the given rectangle, then n(n) represents its area. The triangular number is / of the given area. Therefore, the nn triangular number is.

5 Section 9.3 Probability 359 (d) From part (c), we observe that the nth triangular nn number can be written as. We know that n () n n 0 n n n - n n - p n n n binomial coefficients are the values of n r for r0,,,3,...,n. We can show that nn n as follows: nn n nn -! n -! n!!n -! n!!n -! n So, to find the fourth triangular number, for example, 5 # 4 # 3! compute 4 5! 5!5 -!!3! 5 # (a). (Every other number appears at least twice.) (b) (c) No. (They all appear in order down the second diagonal.) (d) 0. (See Exercise 44 for a proof.) (e) All are divisible by p. (f) Rows that are powers of :, 4, 8, 6, etc. (g) Rows that are less than a power of :, 3, 7, 5, etc. (h) For any prime numbered row, or row where the first element is a prime number, all the numbers in that row (excluding the s) are divisible by the prime. For example, in the seventh row ( ) 7,, and 35 are all divisible by The sum of the entries in the nth row equals the sum of the coefficients in the expansion of (xy) n. But this sum, in turn, is equal to the value of (xy) n when x and y: n n a n 0 b n 0 a n b n- a n b n n p a n n b 0 n a n 0 b a n b a n b p a n n b n 0 n n n - - p n ( ) n n n n - - n 0 - n n p - n n n Section 9.3 Probability Exploration.. 3. n 0 n 4 n p n n n p p p p p p P(±) Pantibody present and 5. P(antibody present ±) P (A little more than chance in 4.) L 0.86 Quick Review C 5,598, C !0 present absent present absent present absent p p p 0.05 p p p p 0.05 p p p p p

6 360 Chapter 9 Discrete Mathematics 8. 5 P C 3 0C 3 5C 0C 5! 3!! 0! 3!7! 5!!3! 0!!8! 9 Section 9.3 Exercises For # 8, consider ordered pairs (a, b) where a is the value of the red die and b is the value of the green die. 4. E{(3, 6), (4, 5), (5, 4), (6, 3)}: P(E) E{both dice even}, {both dice odd}: 3 # 3 3 # 3 P(E) E{(, ), (3, ), (3, ), (4, ), (4, ), (4, 3), (5, ), (5, ), (5, 3), (5, 4), (6, ), (6, ), (6, 3), (6, 4), (6, 5)}: 5 P(E) E{(, ), (, ),...,(6, ), (6, 3)} 30 P(E) # 3 5. P(E) # 3 6. P(E) E{(, ), (, ), (, 4), (, 6), (, ), (, 3), (, 5), (3, ), (3, 4), (4, ), (4, 3), (5, ), (5, 6), (6, ), (6, 5)} 5 P(E) E{(, 6), (, 5), (3, 4), (4, 3), (5, ), (5, 6), (6, ), (6, 5)}: 8 P(E) (a) No The numbers do not add up to. (b) There is a problem with Alrik s reasoning. Since the gerbil must always be in exactly one of the four rooms, the proportions must add up to, just like a probability function. 0. Since 430, we can divide each number in the ratio by 0 and get the proportions relative to the whole. The table then becomes Compartment A B C D Proportion Yes, this is a valid probability function.. P(B or T)P(B)P(T) P(R or G or O)P(R)P(G)P(O) P(R)0. 4. P(not R)-P(R) P[not (O or Y)]-P(O or Y) -(0.0.) P[not (B or T)]-P(B or T)-(0.30.) P(B and B )P(B ) # P(B )(0.3)(0.3) P(O and O )P(O ) # P(O )(0.)(0.) P[(R and G ) or (G and R )]P(R ) # P(G ) P(G ) # P(R )(0.)(0.)(0.)(0.) P(B and Y )P(B ) # P(Y )(0.3)(0.)0.06. P(neither is yellow)p(not Y and not Y ) P(not Y )# P(not Y )(0.8)(0.8)0.64. P(not R and not O )P(not R )# P(not O ) (0.8)(0.9) There are 4 C 6 34,596 possible hands; of these, only consists of all spades, so the probability is. 34, Of the 4 C 6 34,596 possible hands, one consists of all spades, one consists of all clubs, one consists of all hearts, and one consists of all diamonds, so the probability is 4 34,596 33, Of the 4 C 6 34,596 possible hands, there are 4C 4 # 0 C 90 hands with all the aces, so the probability 90 is 34, There are C # C ways to get both black jacks and 4 other cards. Similarly, there are 735 ways to get both red jacks. These two numbers together count twice the C # C # 0 C 90 ways to get all four jacks. Therefore, altogether we have # ,440 distinct ways to have both bowers, so the probability is 4,440 34, (a) A (b) 0.3 (c) 0. (d) 0. PA and B (e) Yes. P(A B) PB 8. (a) A B B PA (b) 0.5 (c) 0. (d) 0. PA and B (e) No. P(A B) Z PA PB P(John will practice)(0.6)(0.8)(0.4)(0.4)0.64

7 Section 9.3 Probability (a) P(meatloaf is served) (b) P(meatloaf and peas are served)(0.0)(0.70) 0.4 (c) P(peas are served)(0.0)(0.70)(0.80)(0.30) If all precalculus students were put on a single list and a name then randomly chosen, the probability P(from Mr. Abel s class girl) would be 6. But when one of the two classes is selected at random, and then a student from this class is selected, P(from Mr. Abel s class girl) Pgirl from Mr. Abel s class Pgirl 3. Within each box, any of the coins is equally likely to be chosen and either side is equally likely to be shown. But a head in the -coin box is more likely to be displayed than a head in the 3-coin box. PH from -coin box P(from -coin box H) PH 3 5 a ba 0 b a ba 0 b a ba0 5 b a ba3 4 b a ba3 4 b a ba3 6 b 3 5 0C C P(none are defective) 4 C 0 # (0.037) 0 (0.963) 4 (0.963) (a) P(cardiovascular disease or cancer) (b) P(other cause of death) P(Yahtzee) 6 # a 5 6 b The sum of the probabilities is greater than an impossibility, since the events are mutually exclusive. 38. P(at least one false positive) -P(no false positives)-(0.993) (a) P(a woman) (b) P(went to graduate school) (c) P(a woman who went to graduate school) (a) (b) (c) 4C C 8 5, C 5 # 6 C 3 40,040 0C 8 5, C 6 # 6 C 4 C 7 # 6 C 4 C 8 # 6 C 0 0C 8 45,045 0, , C This cannot be true. Let A be the event that it is cloudy all day, B be the event that there is at least hour of sunshine, and C be the event that there is some sunshine, but less than hour. Then A, B, and C are mutually exclusive events, so P(A or B or C)P(A)P(B)P(C) P(C)P(C). Then it must be the case that P(C)0. This is absurd; there must be some probability of having more than 0 but less than hour of sunshine. 43. P(HTTTTTTTTT) 44. P(THTTTTHTTT) 45. P(HHHHHHHHHH) a b a b 0 04 a b P(9 H and T) 0C # a 0 b P( H and 8 T) 0C # a 0 b ,640 5, P(3 H and 7 T) 0C 3 # a 0 b P(at least one H)-P(0 H) - 0 C 0 # a 0 b P(at least two H)-P(0 H)-P( H) - 0 C 0 # a 0 b - 0 C # a b False. A sample space consists of outcomes, which are not necessarily equally likely. 5. False. All probabilities are between 0 and, inclusive. 53. Of the 36 different, equally-likely ways the dice can land, 4 ways have a total of 5. So the probability is 4/36/9. The answer is D. 54. A probability must always be between 0 and, inclusive. The answer is E. 55. P(B and A)P(B) P(A B), and for independent events, P(B and A)P(B)P(A). It follows that the answer is A. 56. A specific sequence of one heads and two tails has probability (/) 3 /8. There are three such sequences. The answer is C.

8 36 Chapter 9 Discrete Mathematics 57. (a) (b) (0.37)(0.37)(0.37) 0.05 (c) No. They are more apt to share bagel preferences if they arrive at the store together. 58. (a) P(at least one king)-p(no kings) 48C 5-8,47 5C 5 54,45 L 0.34 (b) The number of ways to choose, e.g., 3 fives and jacks is 4 C 3 # 4 C. There are 3 P 3 # different combinations of cards that can make up the full house, so 3 # # 4 C 3 # 4 C P(full house) 6 5C L (a) We expect (8)(0.3).84 (about ) to be married. (b) Yes, this would be an unusual sample. (c) P(5 or more are married) 8 C 5 # (0.3) 5 (0.77) 3 8 C 6 # (0.3) 6 (0.77) 8 C 7 # (0.3) 7 (0.77) 8 C 8 # (0.3) 8 (0.77) %. 60. (a) 3 C 7 # (0.75) 7 (0.5) % (b) a 3C k # 0.75 k k L % (c) The university s graduation rate seems to be exaggerated; at least, this particular class did not fare as well as the university claims. 6. (a) $.50 (b) 0 6. (a) 9,366,89 L (b) Value Probability (c) 7 k 0 Type of Bagel 3 # 6 - # ,366,809 9,366,89 3,999, ,366,89 3,999,990 # 0 9,366,89-0 # 0 a - 9,366,89 b L (d) In the long run, Gladys is losing $5.73 every time she buys the ten tickets. Given the low probability of a positive payoff, she stands to lose a lot of money if she does this often. Section 9.4 Sequences Probability Plain 0.37 Onion 0. Rye 0. Cinnamon Raisin 0.5 Sourdough 0.5 Quick Review (5-) [(6(5-)4] () # a a 0 5(0-)33 7. a 0 5 # a 0 a ba b a 4 3 ba 5 b a a Section 9.4 Exercises For # 4, substitute n, n,..., n6, and n00.., 3, 4 3, 5 4, 6 5, 7 6 ; ,, 4 5, 3, 4 7, ; , 6, 4, 60, 0, 0; 999, , 6, 6, 4, 0, 6; 9500 For #5 0, use previously computed values of the sequence to find the next term in the sequence. 5. 8, 4, 0, 4; , 7, 7, 7; 67 7., 6, 8, 54; ,.5, 3, 6; 96 9.,,, 0; 3 0., 3,, 4; 3. lim so the sequence diverges. nsq n q,. lim so the sequence converges to 0. nsq n 0, 3., 4, 9, 6,..., n,... lim so the sequence converges to 0. nsq n 0, 4. lim 3n - q, so the sequence diverges. nsq 5. Since the degree of the numerator is the same as the degree of the denominator, the limit is the ratio of the 3n - leading coefficients. Thus lim The nsq - 3n -. sequence converges to. 6. Since the degree of the numerator is the same as the degree of the denominator, the limit is the ratio of the n - leading coefficients. Thus lim The sequence nsq n. converges to. 7. lim so the sequence converges nsq 0.5n lim a n nsq b 0, to lim so the sequence diverges. nsq.5n lim a 3 n nsq b q,

4/17/2012. NE ( ) # of ways an event can happen NS ( ) # of events in the sample space

4/17/2012. NE ( ) # of ways an event can happen NS ( ) # of events in the sample space I. Vocabulary: A. Outcomes: the things that can happen in a probability experiment B. Sample Space (S): all possible outcomes C. Event (E): one outcome D. Probability of an Event (P(E)): the likelihood

More information

STA 2023 EXAM-2 Practice Problems. Ven Mudunuru. From Chapters 4, 5, & Partly 6. With SOLUTIONS

STA 2023 EXAM-2 Practice Problems. Ven Mudunuru. From Chapters 4, 5, & Partly 6. With SOLUTIONS STA 2023 EXAM-2 Practice Problems From Chapters 4, 5, & Partly 6 With SOLUTIONS Mudunuru, Venkateswara Rao STA 2023 Spring 2016 1 1. A committee of 5 persons is to be formed from 6 men and 4 women. What

More information

STA 2023 EXAM-2 Practice Problems From Chapters 4, 5, & Partly 6. With SOLUTIONS

STA 2023 EXAM-2 Practice Problems From Chapters 4, 5, & Partly 6. With SOLUTIONS STA 2023 EXAM-2 Practice Problems From Chapters 4, 5, & Partly 6 With SOLUTIONS Mudunuru Venkateswara Rao, Ph.D. STA 2023 Fall 2016 Venkat Mu ALL THE CONTENT IN THESE SOLUTIONS PRESENTED IN BLUE AND BLACK

More information

Chapter 8 Sequences, Series, and Probability

Chapter 8 Sequences, Series, and Probability Chapter 8 Sequences, Series, and Probability Overview 8.1 Sequences and Series 8.2 Arithmetic Sequences and Partial Sums 8.3 Geometric Sequences and Partial Sums 8.5 The Binomial Theorem 8.6 Counting Principles

More information

Executive Assessment. Executive Assessment Math Review. Section 1.0, Arithmetic, includes the following topics:

Executive Assessment. Executive Assessment Math Review. Section 1.0, Arithmetic, includes the following topics: Executive Assessment Math Review Although the following provides a review of some of the mathematical concepts of arithmetic and algebra, it is not intended to be a textbook. You should use this chapter

More information

Discrete Probability. Chemistry & Physics. Medicine

Discrete Probability. Chemistry & Physics. Medicine Discrete Probability The existence of gambling for many centuries is evidence of long-running interest in probability. But a good understanding of probability transcends mere gambling. The mathematics

More information

Intermediate Math Circles November 8, 2017 Probability II

Intermediate Math Circles November 8, 2017 Probability II Intersection of Events and Independence Consider two groups of pairs of events Intermediate Math Circles November 8, 017 Probability II Group 1 (Dependent Events) A = {a sales associate has training} B

More information

Discrete Random Variables (1) Solutions

Discrete Random Variables (1) Solutions STAT/MATH 394 A - PROBABILITY I UW Autumn Quarter 06 Néhémy Lim Discrete Random Variables ( Solutions Problem. The probability mass function p X of some discrete real-valued random variable X is given

More information

PROBABILITY.

PROBABILITY. PROBABILITY PROBABILITY(Basic Terminology) Random Experiment: If in each trial of an experiment conducted under identical conditions, the outcome is not unique, but may be any one of the possible outcomes,

More information

A Event has occurred

A Event has occurred Statistics and probability: 1-1 1. Probability Event: a possible outcome or set of possible outcomes of an experiment or observation. Typically denoted by a capital letter: A, B etc. E.g. The result of

More information

Year 10 Mathematics Probability Practice Test 1

Year 10 Mathematics Probability Practice Test 1 Year 10 Mathematics Probability Practice Test 1 1 A letter is chosen randomly from the word TELEVISION. a How many letters are there in the word TELEVISION? b Find the probability that the letter is: i

More information

324 Stat Lecture Notes (1) Probability

324 Stat Lecture Notes (1) Probability 324 Stat Lecture Notes 1 robability Chapter 2 of the book pg 35-71 1 Definitions: Sample Space: Is the set of all possible outcomes of a statistical experiment, which is denoted by the symbol S Notes:

More information

Probability the chance that an uncertain event will occur (always between 0 and 1)

Probability the chance that an uncertain event will occur (always between 0 and 1) Quantitative Methods 2013 1 Probability as a Numerical Measure of the Likelihood of Occurrence Probability the chance that an uncertain event will occur (always between 0 and 1) Increasing Likelihood of

More information

Discrete Probability

Discrete Probability Discrete Probability Counting Permutations Combinations r- Combinations r- Combinations with repetition Allowed Pascal s Formula Binomial Theorem Conditional Probability Baye s Formula Independent Events

More information

Probability Year 10. Terminology

Probability Year 10. Terminology Probability Year 10 Terminology Probability measures the chance something happens. Formally, we say it measures how likely is the outcome of an event. We write P(result) as a shorthand. An event is some

More information

Permutation. Permutation. Permutation. Permutation. Permutation

Permutation. Permutation. Permutation. Permutation. Permutation Conditional Probability Consider the possible arrangements of the letters A, B, and C. The possible arrangements are: ABC, ACB, BAC, BCA, CAB, CBA. If the order of the arrangement is important then we

More information

Combinatorics and probability

Combinatorics and probability Combinatorics and probability Maths 4 th ESO José Jaime Noguera 1 Organizing data: tree diagrams Draw the tree diagram for the problem: You have 3 seats and three people Andrea (A), Bob (B) and Carol (C).

More information

3. A square has 4 sides, so S = 4. A pentagon has 5 vertices, so P = 5. Hence, S + P = 9. = = 5 3.

3. A square has 4 sides, so S = 4. A pentagon has 5 vertices, so P = 5. Hence, S + P = 9. = = 5 3. JHMMC 01 Grade Solutions October 1, 01 1. By counting, there are 7 words in this question.. (, 1, ) = 1 + 1 + = 9 + 1 + =.. A square has sides, so S =. A pentagon has vertices, so P =. Hence, S + P = 9..

More information

10.1. Randomness and Probability. Investigation: Flip a Coin EXAMPLE A CONDENSED LESSON

10.1. Randomness and Probability. Investigation: Flip a Coin EXAMPLE A CONDENSED LESSON CONDENSED LESSON 10.1 Randomness and Probability In this lesson you will simulate random processes find experimental probabilities based on the results of a large number of trials calculate theoretical

More information

Probability Year 9. Terminology

Probability Year 9. Terminology Probability Year 9 Terminology Probability measures the chance something happens. Formally, we say it measures how likely is the outcome of an event. We write P(result) as a shorthand. An event is some

More information

1 Preliminaries Sample Space and Events Interpretation of Probability... 13

1 Preliminaries Sample Space and Events Interpretation of Probability... 13 Summer 2017 UAkron Dept. of Stats [3470 : 461/561] Applied Statistics Ch 2: Probability Contents 1 Preliminaries 3 1.1 Sample Space and Events...........................................................

More information

Review Basic Probability Concept

Review Basic Probability Concept Economic Risk and Decision Analysis for Oil and Gas Industry CE81.9008 School of Engineering and Technology Asian Institute of Technology January Semester Presented by Dr. Thitisak Boonpramote Department

More information

2. AXIOMATIC PROBABILITY

2. AXIOMATIC PROBABILITY IA Probability Lent Term 2. AXIOMATIC PROBABILITY 2. The axioms The formulation for classical probability in which all outcomes or points in the sample space are equally likely is too restrictive to develop

More information

Probability and Statistics Notes

Probability and Statistics Notes Probability and Statistics Notes Chapter One Jesse Crawford Department of Mathematics Tarleton State University (Tarleton State University) Chapter One Notes 1 / 71 Outline 1 A Sketch of Probability and

More information

If S = {O 1, O 2,, O n }, where O i is the i th elementary outcome, and p i is the probability of the i th elementary outcome, then

If S = {O 1, O 2,, O n }, where O i is the i th elementary outcome, and p i is the probability of the i th elementary outcome, then 1.1 Probabilities Def n: A random experiment is a process that, when performed, results in one and only one of many observations (or outcomes). The sample space S is the set of all elementary outcomes

More information

P(A) = Definitions. Overview. P - denotes a probability. A, B, and C - denote specific events. P (A) - Chapter 3 Probability

P(A) = Definitions. Overview. P - denotes a probability. A, B, and C - denote specific events. P (A) - Chapter 3 Probability Chapter 3 Probability Slide 1 Slide 2 3-1 Overview 3-2 Fundamentals 3-3 Addition Rule 3-4 Multiplication Rule: Basics 3-5 Multiplication Rule: Complements and Conditional Probability 3-6 Probabilities

More information

PLEASE MARK YOUR ANSWERS WITH AN X, not a circle! 1. (a) (b) (c) (d) (e) 2. (a) (b) (c) (d) (e) (a) (b) (c) (d) (e) 4. (a) (b) (c) (d) (e)...

PLEASE MARK YOUR ANSWERS WITH AN X, not a circle! 1. (a) (b) (c) (d) (e) 2. (a) (b) (c) (d) (e) (a) (b) (c) (d) (e) 4. (a) (b) (c) (d) (e)... Math 020, Exam II October, 206 The Honor Code is in effect for this examination. All work is to be your own. You may use a calculator. The exam lasts for hour 5 minutes. Be sure that your name is on every

More information

Algebra 1 End of Course Review

Algebra 1 End of Course Review 1 Fractions, decimals, and integers are not examples of whole numbers, rational numbers, and natural numbers. Numbers divisible by 2 are even numbers. All others are odd numbers. The absolute value of

More information

12.1. Randomness and Probability

12.1. Randomness and Probability CONDENSED LESSON. Randomness and Probability In this lesson, you Simulate random processes with your calculator Find experimental probabilities based on the results of a large number of trials Calculate

More information

9/6/2016. Section 5.1 Probability. Equally Likely Model. The Division Rule: P(A)=#(A)/#(S) Some Popular Randomizers.

9/6/2016. Section 5.1 Probability. Equally Likely Model. The Division Rule: P(A)=#(A)/#(S) Some Popular Randomizers. Chapter 5: Probability and Discrete Probability Distribution Learn. Probability Binomial Distribution Poisson Distribution Some Popular Randomizers Rolling dice Spinning a wheel Flipping a coin Drawing

More information

Term Definition Example Random Phenomena

Term Definition Example Random Phenomena UNIT VI STUDY GUIDE Probabilities Course Learning Outcomes for Unit VI Upon completion of this unit, students should be able to: 1. Apply mathematical principles used in real-world situations. 1.1 Demonstrate

More information

BASICS OF PROBABILITY CHAPTER-1 CS6015-LINEAR ALGEBRA AND RANDOM PROCESSES

BASICS OF PROBABILITY CHAPTER-1 CS6015-LINEAR ALGEBRA AND RANDOM PROCESSES BASICS OF PROBABILITY CHAPTER-1 CS6015-LINEAR ALGEBRA AND RANDOM PROCESSES COMMON TERMS RELATED TO PROBABILITY Probability is the measure of the likelihood that an event will occur Probability values are

More information

LECTURE NOTES by DR. J.S.V.R. KRISHNA PRASAD

LECTURE NOTES by DR. J.S.V.R. KRISHNA PRASAD .0 Introduction: The theory of probability has its origin in the games of chance related to gambling such as tossing of a coin, throwing of a die, drawing cards from a pack of cards etc. Jerame Cardon,

More information

STP 226 ELEMENTARY STATISTICS

STP 226 ELEMENTARY STATISTICS STP 226 ELEMENTARY STATISTICS CHAPTER 5 Probability Theory - science of uncertainty 5.1 Probability Basics Equal-Likelihood Model Suppose an experiment has N possible outcomes, all equally likely. Then

More information

Introduction and basic definitions

Introduction and basic definitions Chapter 1 Introduction and basic definitions 1.1 Sample space, events, elementary probability Exercise 1.1 Prove that P( ) = 0. Solution of Exercise 1.1 : Events S (where S is the sample space) and are

More information

3.2 Probability Rules

3.2 Probability Rules 3.2 Probability Rules The idea of probability rests on the fact that chance behavior is predictable in the long run. In the last section, we used simulation to imitate chance behavior. Do we always need

More information

1 The Basic Counting Principles

1 The Basic Counting Principles 1 The Basic Counting Principles The Multiplication Rule If an operation consists of k steps and the first step can be performed in n 1 ways, the second step can be performed in n ways [regardless of how

More information

MAT2377. Ali Karimnezhad. Version September 9, Ali Karimnezhad

MAT2377. Ali Karimnezhad. Version September 9, Ali Karimnezhad MAT2377 Ali Karimnezhad Version September 9, 2015 Ali Karimnezhad Comments These slides cover material from Chapter 1. In class, I may use a blackboard. I recommend reading these slides before you come

More information

MATH MW Elementary Probability Course Notes Part I: Models and Counting

MATH MW Elementary Probability Course Notes Part I: Models and Counting MATH 2030 3.00MW Elementary Probability Course Notes Part I: Models and Counting Tom Salisbury salt@yorku.ca York University Winter 2010 Introduction [Jan 5] Probability: the mathematics used for Statistics

More information

Topic -2. Probability. Larson & Farber, Elementary Statistics: Picturing the World, 3e 1

Topic -2. Probability. Larson & Farber, Elementary Statistics: Picturing the World, 3e 1 Topic -2 Probability Larson & Farber, Elementary Statistics: Picturing the World, 3e 1 Probability Experiments Experiment : An experiment is an act that can be repeated under given condition. Rolling a

More information

Chapter 10 Statistics and Probability

Chapter 10 Statistics and Probability Section 0. Probability 367 Chapter 0 Statistics and Probability Section 0. Probability Exploration.. 3. p 0.994 p 0.994 p 0.994 p 0.006 p 0.006 p 0.006 4. P(±)0.00598+0.0490.0089 Pantibody present and

More information

Chapter 4 Probability

Chapter 4 Probability 4-1 Review and Preview Chapter 4 Probability 4-2 Basic Concepts of Probability 4-3 Addition Rule 4-4 Multiplication Rule: Basics 4-5 Multiplication Rule: Complements and Conditional Probability 4-6 Counting

More information

STAT 516 Answers Homework 2 January 23, 2008 Solutions by Mark Daniel Ward PROBLEMS. = {(a 1, a 2,...) : a i < 6 for all i}

STAT 516 Answers Homework 2 January 23, 2008 Solutions by Mark Daniel Ward PROBLEMS. = {(a 1, a 2,...) : a i < 6 for all i} STAT 56 Answers Homework 2 January 23, 2008 Solutions by Mark Daniel Ward PROBLEMS 2. We note that E n consists of rolls that end in 6, namely, experiments of the form (a, a 2,...,a n, 6 for n and a i

More information

MATH 10B METHODS OF MATHEMATICS: CALCULUS, STATISTICS AND COMBINATORICS

MATH 10B METHODS OF MATHEMATICS: CALCULUS, STATISTICS AND COMBINATORICS MATH 10B METHODS OF MATHEMATICS: CALCULUS, STATISTICS AND COMBINATORICS Lior Pachter and Lawrence C. Evans Department of Mathematics University of California Berkeley, CA 94720 January 21, 2013 Lior Pachter

More information

Topic 3: Introduction to Probability

Topic 3: Introduction to Probability Topic 3: Introduction to Probability 1 Contents 1. Introduction 2. Simple Definitions 3. Types of Probability 4. Theorems of Probability 5. Probabilities under conditions of statistically independent events

More information

Statistics for Managers Using Microsoft Excel (3 rd Edition)

Statistics for Managers Using Microsoft Excel (3 rd Edition) Statistics for Managers Using Microsoft Excel (3 rd Edition) Chapter 4 Basic Probability and Discrete Probability Distributions 2002 Prentice-Hall, Inc. Chap 4-1 Chapter Topics Basic probability concepts

More information

7.1 What is it and why should we care?

7.1 What is it and why should we care? Chapter 7 Probability In this section, we go over some simple concepts from probability theory. We integrate these with ideas from formal language theory in the next chapter. 7.1 What is it and why should

More information

Example. What is the sample space for flipping a fair coin? Rolling a 6-sided die? Find the event E where E = {x x has exactly one head}

Example. What is the sample space for flipping a fair coin? Rolling a 6-sided die? Find the event E where E = {x x has exactly one head} Chapter 7 Notes 1 (c) Epstein, 2013 CHAPTER 7: PROBABILITY 7.1: Experiments, Sample Spaces and Events Chapter 7 Notes 2 (c) Epstein, 2013 What is the sample space for flipping a fair coin three times?

More information

Problem # Number of points 1 /20 2 /20 3 /20 4 /20 5 /20 6 /20 7 /20 8 /20 Total /150

Problem # Number of points 1 /20 2 /20 3 /20 4 /20 5 /20 6 /20 7 /20 8 /20 Total /150 Name Student ID # Instructor: SOLUTION Sergey Kirshner STAT 516 Fall 09 Practice Midterm #1 January 31, 2010 You are not allowed to use books or notes. Non-programmable non-graphic calculators are permitted.

More information

Probability deals with modeling of random phenomena (phenomena or experiments whose outcomes may vary)

Probability deals with modeling of random phenomena (phenomena or experiments whose outcomes may vary) Chapter 14 From Randomness to Probability How to measure a likelihood of an event? How likely is it to answer correctly one out of two true-false questions on a quiz? Is it more, less, or equally likely

More information

Outline. Probability. Math 143. Department of Mathematics and Statistics Calvin College. Spring 2010

Outline. Probability. Math 143. Department of Mathematics and Statistics Calvin College. Spring 2010 Outline Math 143 Department of Mathematics and Statistics Calvin College Spring 2010 Outline Outline 1 Review Basics Random Variables Mean, Variance and Standard Deviation of Random Variables 2 More Review

More information

Number Theory and Counting Method. Divisors -Least common divisor -Greatest common multiple

Number Theory and Counting Method. Divisors -Least common divisor -Greatest common multiple Number Theory and Counting Method Divisors -Least common divisor -Greatest common multiple Divisors Definition n and d are integers d 0 d divides n if there exists q satisfying n = dq q the quotient, d

More information

2.6 Tools for Counting sample points

2.6 Tools for Counting sample points 2.6 Tools for Counting sample points When the number of simple events in S is too large, manual enumeration of every sample point in S is tedious or even impossible. (Example) If S contains N equiprobable

More information

Lecture 3. Probability and elements of combinatorics

Lecture 3. Probability and elements of combinatorics Introduction to theory of probability and statistics Lecture 3. Probability and elements of combinatorics prof. dr hab.inż. Katarzyna Zakrzewska Katedra Elektroniki, AGH e-mail: zak@agh.edu.pl http://home.agh.edu.pl/~zak

More information

Name: Exam 2 Solutions. March 13, 2017

Name: Exam 2 Solutions. March 13, 2017 Department of Mathematics University of Notre Dame Math 00 Finite Math Spring 07 Name: Instructors: Conant/Galvin Exam Solutions March, 07 This exam is in two parts on pages and contains problems worth

More information

What is Probability? Probability. Sample Spaces and Events. Simple Event

What is Probability? Probability. Sample Spaces and Events. Simple Event What is Probability? Probability Peter Lo Probability is the numerical measure of likelihood that the event will occur. Simple Event Joint Event Compound Event Lies between 0 & 1 Sum of events is 1 1.5

More information

Chapter 3 : Conditional Probability and Independence

Chapter 3 : Conditional Probability and Independence STAT/MATH 394 A - PROBABILITY I UW Autumn Quarter 2016 Néhémy Lim Chapter 3 : Conditional Probability and Independence 1 Conditional Probabilities How should we modify the probability of an event when

More information

Introduction to Probability, Fall 2009

Introduction to Probability, Fall 2009 Introduction to Probability, Fall 2009 Math 30530 Review questions for exam 1 solutions 1. Let A, B and C be events. Some of the following statements are always true, and some are not. For those that are

More information

Module 8 Probability

Module 8 Probability Module 8 Probability Probability is an important part of modern mathematics and modern life, since so many things involve randomness. The ClassWiz is helpful for calculating probabilities, especially those

More information

UNIT 5 ~ Probability: What Are the Chances? 1

UNIT 5 ~ Probability: What Are the Chances? 1 UNIT 5 ~ Probability: What Are the Chances? 1 6.1: Simulation Simulation: The of chance behavior, based on a that accurately reflects the phenomenon under consideration. (ex 1) Suppose we are interested

More information

CHAPTER - 16 PROBABILITY Random Experiment : If an experiment has more than one possible out come and it is not possible to predict the outcome in advance then experiment is called random experiment. Sample

More information

Nuevo examen - 02 de Febrero de 2017 [280 marks]

Nuevo examen - 02 de Febrero de 2017 [280 marks] Nuevo examen - 0 de Febrero de 0 [0 marks] Jar A contains three red marbles and five green marbles. Two marbles are drawn from the jar, one after the other, without replacement. a. Find the probability

More information

Lecture Slides. Elementary Statistics Eleventh Edition. by Mario F. Triola. and the Triola Statistics Series 4.1-1

Lecture Slides. Elementary Statistics Eleventh Edition. by Mario F. Triola. and the Triola Statistics Series 4.1-1 Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by Mario F. Triola 4.1-1 4-1 Review and Preview Chapter 4 Probability 4-2 Basic Concepts of Probability 4-3 Addition

More information

OCR Statistics 1 Probability. Section 1: Introducing probability

OCR Statistics 1 Probability. Section 1: Introducing probability OCR Statistics Probability Section : Introducing probability Notes and Examples These notes contain subsections on Notation Sample space diagrams The complement of an event Mutually exclusive events Probability

More information

4. Suppose that we roll two die and let X be equal to the maximum of the two rolls. Find P (X {1, 3, 5}) and draw the PMF for X.

4. Suppose that we roll two die and let X be equal to the maximum of the two rolls. Find P (X {1, 3, 5}) and draw the PMF for X. Math 10B with Professor Stankova Worksheet, Midterm #2; Wednesday, 3/21/2018 GSI name: Roy Zhao 1 Problems 1.1 Bayes Theorem 1. Suppose a test is 99% accurate and 1% of people have a disease. What is the

More information

Lecture 2: Probability, conditional probability, and independence

Lecture 2: Probability, conditional probability, and independence Lecture 2: Probability, conditional probability, and independence Theorem 1.2.6. Let S = {s 1,s 2,...} and F be all subsets of S. Let p 1,p 2,... be nonnegative numbers that sum to 1. The following defines

More information

Probability, For the Enthusiastic Beginner (Exercises, Version 1, September 2016) David Morin,

Probability, For the Enthusiastic Beginner (Exercises, Version 1, September 2016) David Morin, Chapter 8 Exercises Probability, For the Enthusiastic Beginner (Exercises, Version 1, September 2016) David Morin, morin@physics.harvard.edu 8.1 Chapter 1 Section 1.2: Permutations 1. Assigning seats *

More information

Answers to All Exercises

Answers to All Exercises CAPER 10 CAPER 10 CAPER10 CAPER REFRESING YOUR SKILLS FOR CAPER 10 1a. 5 1 0.5 10 1b. 6 3 0.6 10 5 1c. 0. 10 5 a. 10 36 5 1 0. 7 b. 7 is most likely; probability of 7 is 6 36 1 6 0.1 6. c. 1 1 0.5 36 3a.

More information

3 PROBABILITY TOPICS

3 PROBABILITY TOPICS Chapter 3 Probability Topics 135 3 PROBABILITY TOPICS Figure 3.1 Meteor showers are rare, but the probability of them occurring can be calculated. (credit: Navicore/flickr) Introduction It is often necessary

More information

Chapter. Probability

Chapter. Probability Chapter 3 Probability Section 3.1 Basic Concepts of Probability Section 3.1 Objectives Identify the sample space of a probability experiment Identify simple events Use the Fundamental Counting Principle

More information

Notes Week 2 Chapter 3 Probability WEEK 2 page 1

Notes Week 2 Chapter 3 Probability WEEK 2 page 1 Notes Week 2 Chapter 3 Probability WEEK 2 page 1 The sample space of an experiment, sometimes denoted S or in probability theory, is the set that consists of all possible elementary outcomes of that experiment

More information

Discrete Structures Homework 1

Discrete Structures Homework 1 Discrete Structures Homework 1 Due: June 15. Section 1.1 16 Determine whether these biconditionals are true or false. a) 2 + 2 = 4 if and only if 1 + 1 = 2 b) 1 + 1 = 2 if and only if 2 + 3 = 4 c) 1 +

More information

14 - PROBABILITY Page 1 ( Answers at the end of all questions )

14 - PROBABILITY Page 1 ( Answers at the end of all questions ) - PROBABILITY Page ( ) Three houses are available in a locality. Three persons apply for the houses. Each applies for one house without consulting others. The probability that all the three apply for the

More information

F71SM STATISTICAL METHODS

F71SM STATISTICAL METHODS F71SM STATISTICAL METHODS RJG SUMMARY NOTES 2 PROBABILITY 2.1 Introduction A random experiment is an experiment which is repeatable under identical conditions, and for which, at each repetition, the outcome

More information

Chapter 2: Probability Part 1

Chapter 2: Probability Part 1 Engineering Probability & Statistics (AGE 1150) Chapter 2: Probability Part 1 Dr. O. Phillips Agboola Sample Space (S) Experiment: is some procedure (or process) that we do and it results in an outcome.

More information

Combinatorics. But there are some standard techniques. That s what we ll be studying.

Combinatorics. But there are some standard techniques. That s what we ll be studying. Combinatorics Problem: How to count without counting. How do you figure out how many things there are with a certain property without actually enumerating all of them. Sometimes this requires a lot of

More information

I - Probability. What is Probability? the chance of an event occuring. 1classical probability. 2empirical probability. 3subjective probability

I - Probability. What is Probability? the chance of an event occuring. 1classical probability. 2empirical probability. 3subjective probability What is Probability? the chance of an event occuring eg 1classical probability 2empirical probability 3subjective probability Section 2 - Probability (1) Probability - Terminology random (probability)

More information

Compound Events. The event E = E c (the complement of E) is the event consisting of those outcomes which are not in E.

Compound Events. The event E = E c (the complement of E) is the event consisting of those outcomes which are not in E. Compound Events Because we are using the framework of set theory to analyze probability, we can use unions, intersections and complements to break complex events into compositions of events for which it

More information

Chapter 5, 6 and 7: Review Questions: STAT/MATH Consider the experiment of rolling a fair die twice. Find the indicated probabilities.

Chapter 5, 6 and 7: Review Questions: STAT/MATH Consider the experiment of rolling a fair die twice. Find the indicated probabilities. Chapter5 Chapter 5, 6 and 7: Review Questions: STAT/MATH3379 1. Consider the experiment of rolling a fair die twice. Find the indicated probabilities. (a) One of the dice is a 4. (b) Sum of the dice equals

More information

TOPIC 12 PROBABILITY SCHEMATIC DIAGRAM

TOPIC 12 PROBABILITY SCHEMATIC DIAGRAM TOPIC 12 PROBABILITY SCHEMATIC DIAGRAM Topic Concepts Degree of Importance References NCERT Book Vol. II Probability (i) Conditional Probability *** Article 1.2 and 1.2.1 Solved Examples 1 to 6 Q. Nos

More information

Basic Concepts of Probability. Section 3.1 Basic Concepts of Probability. Probability Experiments. Chapter 3 Probability

Basic Concepts of Probability. Section 3.1 Basic Concepts of Probability. Probability Experiments. Chapter 3 Probability Chapter 3 Probability 3.1 Basic Concepts of Probability 3.2 Conditional Probability and the Multiplication Rule 3.3 The Addition Rule 3.4 Additional Topics in Probability and Counting Section 3.1 Basic

More information

1 Combinatorial Analysis

1 Combinatorial Analysis ECE316 Notes-Winter 217: A. K. Khandani 1 1 Combinatorial Analysis 1.1 Introduction This chapter deals with finding effective methods for counting the number of ways that things can occur. In fact, many

More information

Statistics for Engineers

Statistics for Engineers Statistics for Engineers Antony Lewis http://cosmologist.info/teaching/stat/ Starter question Have you previously done any statistics? 1. Yes 2. No 54% 46% 1 2 BOOKS Chatfield C, 1989. Statistics for

More information

Ciphering MU ALPHA THETA STATE 2008 ROUND

Ciphering MU ALPHA THETA STATE 2008 ROUND Ciphering MU ALPHA THETA STATE 2008 ROUND SCHOOL NAME ID CODE Circle one of the following Mu Alpha Theta Euclidean Round 1 What is the distance between the points (1, -6) and (5, -3)? Simplify: 5 + 5 5

More information

ELEG 3143 Probability & Stochastic Process Ch. 1 Probability

ELEG 3143 Probability & Stochastic Process Ch. 1 Probability Department of Electrical Engineering University of Arkansas ELEG 3143 Probability & Stochastic Process Ch. 1 Probability Dr. Jingxian Wu wuj@uark.edu OUTLINE 2 Applications Elementary Set Theory Random

More information

STAT 516: Basic Probability and its Applications

STAT 516: Basic Probability and its Applications Lecture 3: Conditional Probability and Independence Prof. Michael September 29, 2015 Motivating Example Experiment ξ consists of rolling a fair die twice; A = { the first roll is 6 } amd B = { the sum

More information

DSST Principles of Statistics

DSST Principles of Statistics DSST Principles of Statistics Time 10 Minutes 98 Questions Each incomplete statement is followed by four suggested completions. Select the one that is best in each case. 1. Which of the following variables

More information

5.3 Conditional Probability and Independence

5.3 Conditional Probability and Independence 28 CHAPTER 5. PROBABILITY 5. Conditional Probability and Independence 5.. Conditional Probability Two cubical dice each have a triangle painted on one side, a circle painted on two sides and a square painted

More information

If the objects are replaced there are n choices each time yielding n r ways. n C r and in the textbook by g(n, r).

If the objects are replaced there are n choices each time yielding n r ways. n C r and in the textbook by g(n, r). Caveat: Not proof read. Corrections appreciated. Combinatorics In the following, n, n 1, r, etc. will denote non-negative integers. Rule 1 The number of ways of ordering n distinguishable objects (also

More information

MTH302 Quiz # 4. Solved By When a coin is tossed once, the probability of getting head is. Select correct option:

MTH302 Quiz # 4. Solved By When a coin is tossed once, the probability of getting head is. Select correct option: MTH302 Quiz # 4 Solved By konenuchiha@gmail.com When a coin is tossed once, the probability of getting head is. 0.55 0.52 0.50 (1/2) 0.51 Suppose the slope of regression line is 20 and the intercept is

More information

THE KENNESAW STATE UNIVERSITY HIGH SCHOOL MATHEMATICS COMPETITION PART I MULTIPLE CHOICE (A) 0 (B) 1 (C) 2 (D) 3 (E) 4

THE KENNESAW STATE UNIVERSITY HIGH SCHOOL MATHEMATICS COMPETITION PART I MULTIPLE CHOICE (A) 0 (B) 1 (C) 2 (D) 3 (E) 4 THE 007 008 KENNESAW STATE UNIVERSITY HIGH SCHOOL MATHEMATICS COMPETITION PART I MULTIPLE CHOICE For each of the following questions, carefully blacken the appropriate box on the answer sheet with a #

More information

Probability Experiments, Trials, Outcomes, Sample Spaces Example 1 Example 2

Probability Experiments, Trials, Outcomes, Sample Spaces Example 1 Example 2 Probability Probability is the study of uncertain events or outcomes. Games of chance that involve rolling dice or dealing cards are one obvious area of application. However, probability models underlie

More information

Topic 4 Probability. Terminology. Sample Space and Event

Topic 4 Probability. Terminology. Sample Space and Event Topic 4 Probability The Sample Space is the collection of all possible outcomes Experimental outcome An outcome from a sample space with one characteristic Event May involve two or more outcomes simultaneously

More information

Algebra II 1.0 MULTIPLE CHOICE. 1. What is the complete solution to the inequality 5x 6 > 9? A. C x > or x < 3. x > 3 or x < B.

Algebra II 1.0 MULTIPLE CHOICE. 1. What is the complete solution to the inequality 5x 6 > 9? A. C x > or x < 3. x > 3 or x < B. lgebra II 1.0 MULTIPLE OIE 1. What is the complete solution to the inequality 5x 6 > 9? x > or x < 3 x > 3 or x < x > 3 or x < ST: (Key)1.0 x < 3 or x > 2. What is the complete solution to the equation

More information

Lecture Slides. Elementary Statistics Tenth Edition. by Mario F. Triola. and the Triola Statistics Series. Slide 1

Lecture Slides. Elementary Statistics Tenth Edition. by Mario F. Triola. and the Triola Statistics Series. Slide 1 Lecture Slides Elementary Statistics Tenth Edition and the Triola Statistics Series by Mario F. Triola Slide 1 4-1 Overview 4-2 Fundamentals 4-3 Addition Rule Chapter 4 Probability 4-4 Multiplication Rule:

More information

HW MATH425/525 Lecture Notes 1

HW MATH425/525 Lecture Notes 1 HW MATH425/525 Lecture Notes 1 Definition 4.1 If an experiment can be repeated under the same condition, its outcome cannot be predicted with certainty, and the collection of its every possible outcome

More information

(a) Fill in the missing probabilities in the table. (b) Calculate P(F G). (c) Calculate P(E c ). (d) Is this a uniform sample space?

(a) Fill in the missing probabilities in the table. (b) Calculate P(F G). (c) Calculate P(E c ). (d) Is this a uniform sample space? Math 166 Exam 1 Review Sections L.1-L.2, 1.1-1.7 Note: This review is more heavily weighted on the new material this week: Sections 1.5-1.7. For more practice problems on previous material, take a look

More information

BINOMIAL DISTRIBUTION

BINOMIAL DISTRIBUTION BINOMIAL DISTRIBUTION The binomial distribution is a particular type of discrete pmf. It describes random variables which satisfy the following conditions: 1 You perform n identical experiments (called

More information

Chapter 2 PROBABILITY SAMPLE SPACE

Chapter 2 PROBABILITY SAMPLE SPACE Chapter 2 PROBABILITY Key words: Sample space, sample point, tree diagram, events, complement, union and intersection of an event, mutually exclusive events; Counting techniques: multiplication rule, permutation,

More information

MATHEMATICS. IMPORTANT FORMULAE AND CONCEPTS for. Summative Assessment -II. Revision CLASS X Prepared by

MATHEMATICS. IMPORTANT FORMULAE AND CONCEPTS for. Summative Assessment -II. Revision CLASS X Prepared by MATHEMATICS IMPORTANT FORMULAE AND CONCEPTS for Summative Assessment -II Revision CLASS X 06 7 Prepared by M. S. KUMARSWAMY, TGT(MATHS) M. Sc. Gold Medallist (Elect.), B. Ed. Kendriya Vidyalaya GaCHiBOWli

More information