Let us think of the situation as having a 50 sided fair die; any one number is equally likely to appear.

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Janice Bruce
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1 Probability_Homework Answers. Let the sample space consist of the integers through. {, 2, 3,, }. Consider the following events from that Sample Space. Event A: {a number is a multiple of 5 5, 0, 5,, } Event B: {a number is odd, 3, 5,, 49} Event C: {a number is a multiple of 7 7, 4, 2,, 49} Event D: {a number is a multiple of 2 2, 4,, } Let us think of the situation as having a sided fair die; any one number is equally likely to appear. a. Are events A and B disjoint? Not disjoint as they share common values such as 5 and 5 for example. b. Are events B and D disjoint? Event D are multiples of 2 which are even numbers, thus they share no common values with Event B, odd numbers. The two events are disjoint. c. What is the probability that one observation results in event A AND B occurring? P(A AND B) Event B: {, 3, 5, 7, 9,, 3, 5, 7, 9, 2, 23,, 27, 29, 3, 33, 35, 37, 39, 4, 43, 45, 47, 49} Event A: {5, 0, 5, 20,, 30, 35, , } The conjunction AND represents what is common between the two sets. P(A AND B) = 5 d. What is the probability that one observation results in event B AND event D occurring? P(B AND D) Event B: {, 3, 5, 7,, 3, 5, 7, 9, 2, 23,, 27, 29, 3, 33, 35, 37, 39, 4, 43, 45, 47, 49} Event D: {a number is a multiple of 2 2, 4,, } Since the two events have nothing in common, then P(B AND D) = 0 e. What is the probability that one observation results in event B and event C occurring? P(B AND C)? Event B: {, 3, 5, 7, 9,, 3, 5, 7, 9, 2, 23,, 27, 29, 3, 33, 35, 37, 39, 4, 43, 45, 47, 49} Event C: {a number is a multiple of 7 7, 4, 2, 28, 35, 42, 49} The conjunction AND represents what is common between the two sets. P(B AND C) = 4

2 f. What is the probability that one observation results in either event B occurring, or event D? P(B OR D)? The two events are disjoint. Thus, it is possible to consider each scenario separately from each other and then combine the results: P(B OR D) = P(B) + P(D) = + The two events are disjoint but represent the whole sample space when put together; basically event D is the even numbers of that set. = g. What is the probability that one observation results in either event A occurring, or event C? P(A OR C)? The two events are not disjoint. Thus, it is not possible to consider each scenario separately from each other and then combine the results: P(A OR C) = P(A) + P(C) = = 7 This is not correct. Event A: {5, 0, 5, 20,, 30, 35, , } Event C: {a number is a multiple of 7 7, 4, 2, 28, 35, 42, 49} Because I can just list out all the values and everything is equally likely it is possible to just count how many values meet the criteria. P(A OR C) = 6 I count 6 unique objects. The general formula that addresses the problem of two events not being disjoint is P(A OR C) = P(A) + P(C) P(A AND C) = = 6 Notice I added the two probabilities for each event, but doing so has made me count the value 35 twice, thus I subtract the count of the common values (the 35 value) to count the common values once, not twice. h. What is the probability that one observation results in either event B occurring, or event C? P(B OR C) The two events are not disjoint. Thus the formula P(B OR C) = P(B) + P(C), does not work. The fact that they share common outcomes makes the above formula invalid. Here is then an approach; brute method.

3 Event B: {, 3, 5, 7, 9,, 3, 5, 7, 9, 2, 23,, 27, 29, 3, 33, 35, 37, 39, 4, 43, 45, 47, 49} Event C: {a number is a multiple of 7 7, 4, 2, 28, 35, 42, 49} Count only each original number once. So for example 7 appears in both B and C, once I counted for one group, I cannot count it again. So how many numbers are we considering? There are 28 numbers. P(B OR C) = 28 If you understand the reason for this brute method, then you understand the meaning of OR, and basic probability which is good. What is a more elegant method? Well it is not much less brute, but it opens a brand new door, that can be then exploited later. Here is the approach: Use the formula I told you not to use, and fix it. P(B OR C) = P(B) + P(C) = + 7 The problem here is that I am counting the numbers 7, 2, 35, and 49 twice if I decide to actually add the fractions. In other words, I am stating that 7, 2, 35 and 49 are more likely to occur than any other number which is not true, since the model concept is a fair sided die. To fix it, remove those common numbers out, and thus the formula becomes. P(B OR C) = P(B) + P(C) P(A and B) = = 28 i. What is the probability that one observation results in either event A occurring, or event B? P(A OR B) Event B: {, 3, 5, 7, 9,, 3, 5, 7, 9, 2, 23,, 27, 29, 3, 33, 35, 37, 39, 4, 43, 45, 47, 49} Event A: {5, 0,. 5, 20,, 30, 35, , } We can answer the question based on counting how many things meet the criteria A OR B. P(A OR B) = 30 We can also use the general formula for A OR B to guide us which still involves counting. P(A OR B) = P(A) + P(B) P(A AND B) 0 5 = + = 30

4 j. A number is chosen at random. It turns out that this number is odd. What is the probability that this number belongs to set A? P(A odd number)? Odd number: {, 3, 5, 7, 9,, 3, 5, 7, 9, 2, 23,, 27, 29, 3, 33, 35, 37, 39, 4, 43, 45, 47, 49} Event A: {5, 0, 5, 20,, 30, 35, , } Because the situation is simple to visualize we can just count what values meet the criteria. P(A odd number) = 5 Notice that we are only dealing with odd numbers, thus our sample space consists of numbers, and 5 of those numbers can be found in event A. Here is the same thing but using the formula P(A odd number) = = ( ) P( odd number) P A AND odd number 5 = 5 k. A number is chosen at random. It turns out it belongs to set B. What is the probability it also belongs to set C? P(C B)? Event B: {, 3, 5, 7, 9,, 3, 5, 7, 9, 2, 23,, 27, 29, 3, 33, 35, 37, 39, 4, 43, 45, 47, 49} Event C: {a number is a multiple of 7 7, 4, 2, 28, 35, 42, 49} P(C B) = 4 2. Heights of women. The heights of women aged 20 to 29 are approximately Normal with mean 64 inches and standard deviation 2.7 inches. Men the same age have mean height 69.3 inches with standard deviation 2.8 inches, also normally distributed. Let the random variable Y determine the height of a woman in inches. a. What is the probability that a randomly chosen woman is either shorter than 60 inches, or taller than 69 inches? Let the random variable Y measure the height of a woman. The events are disjoints thus I can calculate each event separately and add the results.

5 P(Y < 60 OR Y > 69) = P(Y < 60) + P( Y > 69 ) = P Z < + P Z > = P(Z < -.48) + P(Z >.85) = normsdist(-.48) + normsdist(.85) =normalcdf(-0, -.48) + normalcdf(.85,0) = = 0.06 Note: P(Z <.85) = , so P(Z >.85) = = b. What is the probability that a randomly chosen woman is over 64 inches tall and less than 70 inches tall? The events are not disjoint, and I will find the region that is common to both. P(Y > 64 AND Y < 70) = P(64 < Y < 70) Restate the question. = P(Y < 70) - P(Y < 64) Represents what I will have to do to answer question = P Z < = P(Z < 2.22) =normsdist(2.22) 0.5 =normalcdf(-0, 2.22) 0.5 = = c. What is the probability that a randomly chosen woman is 65 inches or taller and less than 60 inches? Let the random variable Y be the height of a randomly chosen woman. P(Y > 65 and Y < 60) = 0, since one person cannot satisfy both criteria simultaneously. d. Are the events mentioned in c disjoint? Yes, since one person cannot satisfy both criteria simultaneously.

e. Let the random variable X measure the height of a male in inches. Calculate P(X > 75.4 OR X < 69.3). Men the same age have mean height 69.3 inches with standard deviation 2.8 inches. P(X > 75.4 OR X < 69.3) = P(X > 75.

6 e. Let the random variable X measure the height of a male in inches. Calculate P(X > 75.4 OR X < 69.3). Men the same age have mean height 69.3 inches with standard deviation 2.8 inches. P(X > 75.4 OR X < 69.3) = P(X > 75.4) + P(X < 69.3) Events are disjoint so we can separate. = P Z > P Z < 2.8 = P(Z > 2.8) = normsdist(2.8) = normalcdf(2.8, 0) = Note: P(Z < 2.8) = , so P(Z > 2.8) = =.046 = I set the random number generator in Excel to generate random numbers from a uniform distribution. The computer can generate any real numbers between 5 and 30. The random variable X represents all the random numbers generated by the computer. a. What is the sample space of the random variable X? σ x = 7.22, µ x = 7.5 All the real numbers between 5 and 30 including 5 and X b. What is the probability that a random number generated by the computer program is either less than 2 or greater than 22? P(X < 2 or X > 22) = P(X < 2) + P( X > 22) The two events are disjoint = (2 5) + (30 22) = = 0.6 σ x = 7.22, µ x = X c. What is the probability that a random number generated by the computer is either greater than 5 or less than 20? P(X > 5 or X < 20) = σ x = 7.22, µ x = 7.5 Since, as you can see from the picture X> 5 or X < 20 encompasses X

7 the entire sample space. P(X > 5 or X < 20) = P(5 < X < 30) = d. What is the probability that a random number generated by the computer is both less than 5 and more than 29? P(X < 5 and X > 29) = 0 One observation cannot satisfy both events simultaneously. σ x = 7.22, µ x = 7.5 e. Are the events mentioned in part d disjoint? Yes, one number generated at random cannot satisfy both events simultaneously. f. P(X < 24 AND X > 20) = P(20 < X < 24) Restate the question = (24 20) = X σ x = 7.22, µ x = X 4. A coin is tossed 2 times into the air. The random variable X counts the number of times that a coin lands heads. Write down the sample space of the random variable X. {0,, 2, 3, 4, 5, 6, 7, 8, 9, 0,, 2} 5. A MTH 243 class has 35 students. Out of those 35 students 8, have taken the course the previous term but did not pass. The instructor for the class will sample 6 students at random and look at their transcripts. Let the random variable Y count the number of students out of the sample of six that did not pass the previous term. Write down the sample space of the random variable Y. {0,, 2, 3, 4, 5, 6} 6. A test is created to test if a person has been infected with HIV. The test is an over the counter exam, performed by the individual. If a person is infected it will detect this 80% of the time. Suppose that five people with HIV are tested using this exam. Let the random variable H count how many out of the five are correctly identified as having HIV. Below are the probability values of the random variable H, except for one. H P(x)

8 a. What is the probability that all of the five are correctly identified? ( ) = The sum must always equal. b. What is the sample space of the random variable H? {0,, 2, 3, 4, 5} c. What is the probability that out of a sample of five either or 4 people have been detected as having an HIV infection? P(H = or H = 4) = P(H = ) + P(H = 4) Events are disjoint since a sample (one observation will only be = able to yield one number. = 0.46 d. Out of a single sample of five HIV infected people, calculate P(H = 0 AND H = 3)? P(H = 0 AND H = 3) = 0 since one observation (recall one observation consist of the result of testing five individuals) cannot satisfy both events simultaneously. e. Calculate P(H = 2 or H = 4 or H = 5) = P(H = 2) + P(H = 4) + P(H = 5) Events are disjoint. = =

The enumeration of all possible outcomes of an experiment is called the sample space, denoted S. E.g.: S={head, tail}

The enumeration of all possible outcomes of an experiment is called the sample space, denoted S. E.g.: S={head, tail} Random Experiment In random experiments, the result is unpredictable, unknown prior to its conduct, and can be one of several choices. Examples: The Experiment of tossing a coin (head, tail) The Experiment