MTH152-QA8

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course MTH 152

Time: 9:40 PMDate: 7/17

If your solution to stated problem does not match the given solution, you should self-critique per instructions at

http://vhcc2.vhcc.edu/dsmith/geninfo/labrynth_created_fall_05/levl1_22/levl2_81/file3_259.htm.

Your solution, attempt at solution.

If you are unable to attempt a solution, give a phrase-by-phrase interpretation of the problem along with a statement of what you do or do not understand about it. This response should be given, based on the work you did in completing the assignment, before you look at the given solution.

008. Conditional probabilities, more probabilities

STUDENT QUESTION: Mr Smith I am just a little confused on how you know what formula to use and when to use it. Do you use combination or Conditional probability etc.?

INSTRUCTOR'S RESPONSE: If the problem can be formulated as 'what is the probability of a certain event, given that some condition holds', then it's a conditional probability. P(B | A) = P(A ^ B) / P ( A ).

Either or both of the probabilities P(A ^ B) and P(B) might be determined by the fundamental counting principle, permutations or combinations.

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Question: `q001. Note that there are 9 questions in this assignment.

Suppose that a card is dealt from a well-shuffled deck, and that you can tell by the reflection in your opponent's reading glasses that the card is a red face card. However you can't tell any more than that.

What is the probability that the card is the Jack or the Queen of Diamonds?

YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY

Your solution:

- If we see that it is a red face card, that pretty much reduces the possibilities to hearts or diamonds, and Jack King and Queen.

Jack (hearts)

Jack (diamonds)

King (hearts)

King (diamonds)

Queen (hearts)

Queen (diamonds)

- So we see that there are six possibilities in which the card is a red face card, and there are two options for the card being the Jack/Queen of diamonds, represented by 2/6 or 1/3, = 33.3%

confidence rating #$&*:

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Given Solution: In this case your knowledge that the card is a red face card limits the possibilities to six: The Jack of Hearts or Diamonds, the Queen of Hearts or Diamonds, or the King of Hearts or Diamonds. The probability that the card is one of the two specified cards is therefore 2 / 6 = 1/3.

Note that without any limits on the possibilities, the probability that the card is the Jack or Queen of Diamonds is only 2 / 52 = 1 / 26. Note also that the probability that a card is a red face card is 6 / 52 = 3/26. If we divide the first probability by the second we get 1/26 / ( 3/26) = 1/26 * 26/3 = 1/3.

Thus the probability that a card is the Jack or Queen of Diamonds, given that it is a red face card, is equal to the probability that it is the Jack or Queen of Diamonds (and a face card), divided by the probability that it is a red face card.

This statement has the form 'The probability of B, given A, is equal to the probability of A ^ B divided by the probability of A'. This statement is abbreviated to the form

P(B | A) = P(A ^ B) / P(A).

This is the formula for Conditional Probability. In this problem the outcome was Jack or Queen of Diamonds, and the condition was that we have a red face card.

Self-critique: Okay. In the above statement P (B | A) = P(A ^ B) / P(A) what does the B and A symbolize? Are they events A or B? I’m attempting to use the formula above for the problem rather than simply seeing the list.

@&

B is the event that the card is the Jack or Queen of diamonds.

A is the event that the card is a red face card.

A ^ B is the event that the card is a red face card, and it the Jack or Queen of diamons. Since the Jack and Queen of diamonds are red face cards, the event B is a subset of the event A, so A ^ B is just the same as B.

The probability of event B is 1 / 26.

The probability of event A is 6/52 = 3/26.

The probability of A, given B, is

P(B | A) = P(A ^ B) / P( A ) = 1/26 / (3/26) = 1/3.

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Also, in the statement 'The probability of B, given A, is equal to the probability of A ^ B divided by the probability of A'. Is the denominator thus / P(A) or / P(A’)? Since the ‘ shows a complement (or maybe negation? Exact opposite?) and its nature as the denominator, does this then reverse since it’s theoretically the reciprocal?

I.e. P (B | A) = P (A ^ B) / P (A) vs. P(B |A) = P(A ^ B) / P(A’)

I would think that, given P(A’) is understood to be any number over /1, and it takes the form 1/ P(A) I hypothesize that this thus

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Self-critique rating: Okay. See my comment/hypothesis above.

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Question: `q002. Suppose that a face card is the first card dealt from a full deck of well-shuffled cards. What is the probability that the next card dealt (without replacement) will also be a face card?

YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY

Your solution:

- There are 3 separate types of face cards, and four suits in which they reside, leaving a total of 12 face cards out of 52. Since one has already been chosen that leaves 11 out of 52.

confidence rating #$&*:

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Given Solution: We know that after the first card is dealt there are 11 face cards left out of the original 12, and 51 cards left in the deck. The probability is therefore obviously 11/51.

We can also analyze this situation as a conditional probability. B stands for 'a face card is dealt on the second card' while A stands for 'a face card is dealt on the first card'. So the event A ^ B stands for 'a face card is dealt on the first card and on the second', with probability 12/52 * 11/51. A stands for 'a face card is dealt on the first card', with probability 12 / 52. So P(B | A) stands for 'a face card is deal on the second card given that a face card is dealt on the first'.

By the formula we have P(B | A) = P ( A ^ B ) / P(A) = [ 12 / 52 * 11 / 51 ] / [ 12 / 52 ] = 11 / 51, which of course we already knew from direct analysis.

Self-critique: Okay.

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Self-critique rating: Okay.

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Question: `q003. Given that the first clip of a coin is Heads, what is the probability that a five-flip sequence will result in exactly four Heads?

YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY

Your solution:

- Given that the first flip is heads will be denoted by the variable A, where the desired event “with the first flip being heads, resulting in exactly four heads” will be denoted as B.

- There are 2^5 = 32 possible outcomes.

- Approximately half of 32 is estimated to begin with an H (theorized from 32 / 2 = 16, where 2 denotes the number of sides on a coin)

- So this translates into the formula as

P(B|A) = P(A^B) / P(A)

- P(B|A) = (4/32) / (1/2) &&&& How can I find 4/32 without direct analysis?&&&&

@&

Having obtained 'heads' on the first flip, in order to get a total of 4 'heads' you must get 3 'heads' on the remaining 4 flips. There are C(4, 3) = 4 ways this could happen.

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= 4/16 = ¼ = 25% chance.

confidence rating #$&*:

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Given Solution: If we were to list the 2^5 = 32 possible outcomes for five flips, we would find that 16 of them have 'heads' on the first flip, and that of these 16 there are 4 outcomes with exactly four 'heads'. The probability therefore looks like 4 / 16 = 1/4, which is correct.

To verify this by the formula P( B | A ) = P( A ^ B) / P(A), we let B stand for the desired event of exactly four 'heads' and A for the 'given' event of 'heads' on the first flip. On five flips, P(A) = 16 / 32 = 1/2 (probability of 'heads' on the first flip), which P(B ^ A) = 4 / 32 (four of the 32 possible outcomes have 'heads' on the first flip and exactly four 'heads').

The formula therefore gives us P( B | A ) = P( A ^ B) / P(A) = (4/32) / (2/1) = (4 / 32) * (2 / 1) = 4 / 16 = 1/4.

Self-critique: Note my comment regarding the discovery of 4/32 using mathematics. Through observation I could see that 4 outcomes out of the 32 would begin with H and contain 3 additional H’s shown by (H, H, H, H, T) , (H, T, H, H, H) , (H, H, H, T, H) and (H, H, T, H, H). How would one find this by math means? Of course this wouldn’t be very time-consuming to list the outcomes, given the nature of the question; H’s have to be first, and there must be 4 H’s altogether

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Self-critique rating: Okay. See my comment listed within &&&& in Your Solution and Self-Critique.

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Question: `q004. Given that the first of two dice comes up even, what is the probability that the total on the two dice will be greater than 9? How does this compare with the unconditional probability that the total of two fair dice will be greater than 9?

YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY

Your solution:

- With any two rolls of dice, being six sided, there are a possible of 36 outcomes. In order for the result to be greater than 9, one must roll numbers > 2, 4 so the possible outcomes would be

(4,5) , (6, 3) , (3, 6) and (5,4).

- Of those outcomes, only two show an even number being rolled on the first of two dice.

- So the probability would be shown as 2/36, or 1/18 = 55.6% chance of rolling a die with an even number first whose sum will be 9.

- However, this is the case will = 9.

- In order to get an outcome with an even number first and being greater than or equal to 9, one must roll:

(4, 5) , (4, 6) , (6, 3) , (6, 4) , (6, 5) , (6, 6) so 6/36 or 1/6 = 16.7% chance.

confidence rating #$&*:

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Given Solution: We can list the sample space of dice possibilities for which the first number is even. The sample space is { (2,1), (2,2), (2,3), (2,4), (2,5), (2,6), (4,1), (4,2), (4,3), (4,4), (4,5), (4,6), (6,1), (6,2), (6,3), (6,4), (6,5), (6,6) }. We note that there are 18 elements in the sample space.

We then find the corresponding totals, which are

3, 4, 5, 6, 7, 8

5, 6, 7, 8, 9, 10

7, 8, 9, 10, 11, 12.

Of these 18 totals, 4 are greater than 9. Thus the probability that the total of two dice will be greater than 9, given that the first is even, is 4/18 = 2/9.

To verify this by the formula P( B | A ) = P( A ^ B) / P(A), we let B stand for the set of all dice pairs which give a total greater than 9, and A for the set of all dice pairs where the first die shows an even number. We have seen that A = { (2,1), (2,2), (2,3), (2,4), (2,5), (2,6), (4,1), (4,2), (4,3), (4,4), (4,5), (4,6), (6,1), (6,2), (6,3), (6,4), (6,5), (6,6) }.

Listing the elements in B we find that B = { (4, 6), (6, 4), (5, 5), (6, 5), (5, 6), (6, 6) }. There are 6 elements in this set.

A ^ B consists of the set of elements common to both A and B, or { (4, 6), (6, 4), (6,5), (6, 6) }.

Since there are 4 elements in A ^ B, 18 elements in A, and 36 elements in the sample space for two dice, it follows that

P(A) = 18 / 36 = 1/2 and P(A ^ B) = 4 / 36 = 1/9.

Therefore the probability we are looking for, P(B | A), is given by

P(B | A) = P(A ^ B) / P(A) = (1/9) / (1/2) = (1/9) * (2/1) = 2/9.

This is in agreement with the previous result obtained by listing.

STUDENT QUESTION

I understood this but I’m confused about where the 36 examples in the sample space come from

in the probability formula?

INSTRUCTOR RESPONSE

If you list all the possible outcomes for 2 dice, you find that there are 36 possibilities.

They can be listed in a table with 6 columns and 6 rows.

Self-critique: Interesting. I love how things play out with math. Analyze and correct as necessary, and I’ll do the same.

- I can understand that, when one lists out the possibilities of possible outcomes starting with an even number will be (1,1) . . . (6, 6) there will be 36 outcomes, 18 of which have an even number rolled first, and 4 of which will produce a sum > 9. Thus 4/18 = 2/9 =22.2%

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Self-critique rating: Good to go. See my comment listed above.

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Question: `q005. A spinner has numbers 2, 3, 4, 5 and 6. Given that the first number is odd, what is the probability that the sum of the results on two consecutive spins is even?

YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY

Your solution:

- I begin by listing all the possible outcomes from (2, 2) . . . (6, 6). = 25 possible outcomes.

- I note that 10 out of the 25 begin with an odd number, denoting A = 10/25

- Out of those 10, 4 result in an even number, denoting B = 4/10 = 2/5

- Using the Conditional Probability Formula (hereafter known as CPF):

- P(B|A) = P(A^B) / P(A)

= (4/25) / (2/5)

= 2/5 = .4 = 40%

confidence rating #$&*:

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Given Solution: The set of possibilities for which the first number is odd is { (3, 2), (3, 3), (3, 4), (3, 5), (3, 6), (5, 2), (5, 3), (5, 4), (5, 5), (5, 6) }. There are therefore 10 possibilities. Of these 4 add up to an even total, so the probability that the total is even, given that the first number is odd, is

Probability of B given A = 4/10 = 2/5.

To verify this by the formula P( B | A ) = P( A ^ B) / P(A), we let B stand for the set of all pairs that add up to an even number and A for the set of all pairs for which the first number is even. The sample space for two spins has 5 * 5 = 25 elements. Of these, only the four outcomes (3, 3), (3, 5), (5, 3) and (5, 5) for which both spinners land on odd numbers are in the set A ^ B. Thus

P(A | B) = 4/25.

The set A consists of the 10 pairs listed earlier. So

P(A) = 10/25 = 2/5.

Thus

P(B | A) = P(A ^ B) / P(A) = (4/25) / (2/5) = (4/25) * (5/2) = 2/5

in agreement with our previous result.

Self-critique: Nailed it. I’m getting a better idea of direct analysis vs. conditional probability, and using them not interchangeably but rather in coordination with one another.

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Self-critique rating: Okay, see my comment/Update to Comprehension above.

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Question: `q006. What is the probability that two consecutive cards dealt (without replacement) from a full deck will both be Hearts?

YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY

Your solution:

- There are 52 cards in a standard deck, and if two cards are dealt without replacement this number becomes 50.

- There are approximately 13/52 hearts in a deck of cards, when the second is chosen it becomes 12/52.

- Any of the hearts could be chosen, without regard to order (given its random nature) so C(13,2) = 78

- But to describe the two hearts being taken from the suit, FROM the deck of cards, one must determine the possibility, as a number, of how many outcomes one could produce from selecting 2 from 52, described as C(52,2) = 1326

- In order to determine the probability of selecting two heart cards from a deck, one must divide the number of possibilities of choosing 2 heart cards from a suit of 13, by the number of possibilities one has of drawing two cards from a 52-card deck.

- 78/1326 = ~59%

confidence rating #$&*:

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Given Solution: When the first card is dealt there are 13 Hearts in a deck of 52. When the second card is dealt there are 12 Hearts left in the remaining 51 cards. The order in which the cards are dealt does not matter, and there are two possible orders for any 2-card 'hand'. The number of ways to get 2 Hearts is therefore C(13,2) = 13 * 12 / 2 = 156 / 2 = 78.

The number of possible 2-card 'hands' is C(52, 2) = 52 * 51 / 2 = 1326.

The probability of obtaining two Hearts is therefore 78 / 1326, which can be reduced or expressed as a decimal.

STUDENT COMMENT

The part I find trickiest is to remember to

divide the 13*12 by 2 and the 52*51 by 2 because I seem to forget to do so.

INSTRUCTOR RESPONSE

Remember that in this case the order in which the cards are dealt doesn't matter; the player can rearrange them in any way he or she chooses.

You therefore need to divide by the number of possible orders.

Self-critique:

So if I wanted to describe the probability of choosing three consecutive spades from a well-shuffled deck of cards, I would say that there are C(13,3) = 286 possible ways to choose three cards from a spade suit of 13, then C(52,3) = 22100 possible ways to choose three cards from a deck of 52 then divide the quotients to produce a 1.3% chance?

- Taken from the math of:

- C(13,3) = 286 / C(52,3)= 22100  286/22100 = 0.0129411765 = 1.3%

@&

Very good.

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Self-critique rating: Okay. See my extra practice problem above.

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Question: `q007. What is the probability that two consecutive cards dealt (without replacement) from a full deck will both be of the same suit?

YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY

Your solution:

- Any two cards taken from a deck of 52 must be described by the suit in which they belong.

- My first instinct is to assume that this relates to the previous problem. But, to recall from a previous assignment, when selecting probability of getting a two-pair hand, after one describes the two pairs one must consider any of the 44 remaining, described as C(44,1)

- C(13,2) * 4 = .23529 = 23.5%

@&

The first card is whatever suit is happens to be.

This leaves 51 cards, 12 of which are of the desired suit.

So the probability that the second matches the first is 12 / 51 = 4/17, pretty close to 23.5%.

*@

confidence rating #$&*:

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Given Solution: A quick common-sense solution tells us that sense the first card can be anything, then since of the 51 remaining cards, there remain remain 12 cards that match the suit of the first the probability must be 12/51 = 4/17.

STUDENT QUESTION

For the previous problem, we used two hearts, so how come this problem

isn’t completed the same way that the last one was, given that we are finding 2 of the same suit?

INSTRUCTOR RESPONSE

In the preceding problem the suit was specified. The condition couldn't be satisfied unless the first card was a heart.

In this problem any first card is OK; the only condition is that the second card be of the same suit. So the probability here is significantly higher.

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Question: `q008. On a roll of two dice, what is the probability that one of the numbers is a 6, given that the total is 10?

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Your solution:

- If the total is 10 (assuming the sum) and one of the numbers is a 6, this points to the other number being a 4.

- The number of outcomes that can equal 10 are:

- (5,5) , (6, 4) , (4,6) giving three outcomes. One of which has neither a 6 or a 4 so there are two outcomes out of the three possible with a 6, so 2/3 = .66666667 = 67% chance

@&

Good.

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confidence rating #$&*:

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Self-critique Rating:

&#This looks good. See my notes. Let me know if you have any questions. &#