MTH 245 Notes Theoretical Probability Assignment

MTH 245 Notes Theoretical Probability Assignment

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MTH 245 Lesson 10 Notes Theoretical Probability

The theoretical probability approach is used when 𝑆𝑆 consists of a reasonably small number of countable outcomes, each of which is equally likely to occur.

There are three steps to calculating a theoretical probability:

1. Define the experiment, the sample space 𝑆𝑆, and the event space 𝐴𝐴. 2. For both 𝐴𝐴 and 𝑆𝑆, count the number of outcomes in each. 3. Calculate the probability:

𝑃𝑃(𝐴𝐴) = number of outcomes in 𝐴𝐴 number of outcomes in 𝑆𝑆

Warning! This approach assumes that each outcome in 𝑆𝑆 is equally likely. If that isn’t the case, then the above formula does not produce the correct results. Example 1: To continue Example 1 in Lesson 9, suppose we roll a single six- sided die once. What is the probability of rolling greater than a 4?

We have already defined the sample space as 𝑆𝑆 = {1, 2, 3, 4, 5, 6} and the event space as 𝐴𝐴 = {5, 6}. It follows that

𝑃𝑃(𝐴𝐴) = 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 π‘œπ‘œπ‘œπ‘œ π‘œπ‘œπ‘›π‘›π‘œπ‘œπ‘œπ‘œπ‘œπ‘œπ‘›π‘›π‘›π‘›π‘œπ‘œ 𝑖𝑖𝑛𝑛 𝐴𝐴 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 π‘œπ‘œπ‘œπ‘œ π‘œπ‘œπ‘›π‘›π‘œπ‘œπ‘œπ‘œπ‘œπ‘œπ‘›π‘›π‘›π‘›π‘œπ‘œ 𝑖𝑖𝑛𝑛 𝑆𝑆

= 2 6

= 1 3

= 0.333 .

Example 2: Consider an experiment where a fair coin is flipped three times in a row and the result of each set of flips is recorded as a single sequence. What is the probability that the next sequence of flips will contain two or more “tails?”

There are eight possible sequences of flips: 𝑆𝑆 = {𝐻𝐻𝐻𝐻𝐻𝐻, 𝑇𝑇𝐻𝐻𝐻𝐻, 𝐻𝐻𝑇𝑇𝐻𝐻, 𝐻𝐻𝐻𝐻𝑇𝑇, 𝑇𝑇𝑇𝑇𝐻𝐻, 𝑇𝑇𝐻𝐻𝑇𝑇, 𝐻𝐻𝑇𝑇𝑇𝑇, 𝑇𝑇𝑇𝑇𝑇𝑇}. Of these, four contain two or more “tails”: 𝐴𝐴 = {𝑇𝑇𝑇𝑇𝐻𝐻, 𝑇𝑇𝐻𝐻𝑇𝑇, 𝐻𝐻𝑇𝑇𝑇𝑇, 𝑇𝑇𝑇𝑇𝑇𝑇}. Therefore, 𝑃𝑃(𝐴𝐴) = 4

8 = 1

2 = 0.500.

The Addition Rule

A compound event is an event that combines two or more simple events.

The compound event 𝐴𝐴 βˆͺ 𝐡𝐡 (read “A union B” or “A or B”) is the outcome where, in a single trial, either 𝐴𝐴 occurs or 𝐡𝐡 occurs or they both occur. If A and B can both occur, then their intersection 𝐴𝐴 ∩ 𝐡𝐡 (read “A intersect B” or “A and B”) is not empty and contains outcomes that are in both A and B.

To calculate the probability of 𝐴𝐴 βˆͺ 𝐡𝐡 occurring, count the number of ways 𝐴𝐴 can occur and the number of ways 𝐡𝐡 can occur, and add those totals together in such a way that no individual outcome is counted twice. Then divide that sum by the total number of possible outcomes. Formally, this process is represented by the Addition Rule:

For any two events A and B,

𝑃𝑃(𝐴𝐴 βˆͺ 𝐡𝐡) = 𝑃𝑃(𝐴𝐴) + 𝑃𝑃(𝐡𝐡)βˆ’ 𝑃𝑃(𝐴𝐴 ∩ 𝐡𝐡)

Subtracting the term P(𝐴𝐴 ∩ 𝐡𝐡) ensures we don’t double count the outcomes that appear in both A and B when calculating P(𝐴𝐴 βˆͺ 𝐡𝐡). Example 4: Continuing Example 1 of this section, what is the probability rolling greater than a 4 or an even number?

We already know that 𝑆𝑆 = {1, 2, 3, 4, 5, 6} and 𝐴𝐴 = {5, 6}. In addition, define 𝐡𝐡 = {𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑒𝑒𝑛𝑛𝑛𝑛𝑛𝑛𝑒𝑒𝑛𝑛𝑛𝑛} = {2, 4, 6}. Then 𝐴𝐴 ∩ 𝐡𝐡 = {6} and

𝑃𝑃(𝐴𝐴 βˆͺ 𝐡𝐡) = 𝑃𝑃(𝐴𝐴) + 𝑃𝑃(𝐡𝐡) βˆ’ 𝑃𝑃(𝐴𝐴 ∩ 𝐡𝐡) = 2 6

+ 3 6 βˆ’ 1

6 = 4

6 = 2

3 = 0.333 .

Example 4: A sample of 200 tennis rackets – 100 graphite and 100 wood – is taken from the warehouse. Suppose 6 of the wood rackets and 9 of the graphite rackets are defective. If one racket is randomly selected from the sample of 200, find the probability that the racket is either wood or defective.

Define 𝐴𝐴 = {100 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 π‘›π‘›π‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘’π‘’π‘Ÿπ‘Ÿπ‘›π‘›}, 𝐡𝐡 = {15 π‘€π‘€π‘’π‘’π‘‘π‘‘π‘’π‘’π‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘‘π‘‘π‘’π‘’π‘’π‘’ π‘›π‘›π‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘’π‘’π‘Ÿπ‘Ÿπ‘›π‘›}, and 𝐴𝐴 ∩ 𝐡𝐡 = {6 π‘›π‘›π‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘’π‘’π‘Ÿπ‘Ÿπ‘›π‘› π‘Ÿπ‘Ÿβ„Žπ‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿ π‘Ÿπ‘Ÿπ‘›π‘›π‘’π‘’ π‘›π‘›π‘€π‘€π‘Ÿπ‘Ÿβ„Ž 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 π‘Ÿπ‘Ÿπ‘’π‘’π‘€π‘€ π‘€π‘€π‘’π‘’π‘‘π‘‘π‘’π‘’π‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘‘π‘‘π‘’π‘’π‘’π‘’}. Then

𝑃𝑃(𝐴𝐴 βˆͺ 𝐡𝐡) = 𝑃𝑃(𝐴𝐴) + 𝑃𝑃(𝐡𝐡)βˆ’ 𝑃𝑃(𝐴𝐴 ∩ 𝐡𝐡) = 100 200

+ 15 200

βˆ’ 6 200

= 109 200

= 0.545. Example 5: Refer to the table below. If 1 subject is selected at random from among 1,000 subjects given a drug test, what is the probability that the subject had a positive drug test, actually uses drugs, or both?

Positive

Test Result Negative

Test Result Total

Subject uses drugs 44 6 50 Subject doesn’t use drugs

90 860 950

Total 134 866 1,000

Define 𝐴𝐴 = {134 π‘€π‘€β„Žπ‘€π‘€ π‘Ÿπ‘Ÿπ‘’π‘’π‘›π‘›π‘Ÿπ‘Ÿπ‘’π‘’π‘€π‘€ π‘π‘π‘€π‘€π‘›π‘›π‘‘π‘‘π‘Ÿπ‘Ÿπ‘‘π‘‘π‘’π‘’π‘’π‘’}, 𝐡𝐡 = {50 π‘€π‘€β„Žπ‘€π‘€ 𝑛𝑛𝑛𝑛𝑒𝑒 𝑀𝑀𝑛𝑛𝑛𝑛𝑑𝑑𝑛𝑛}, and 𝐴𝐴 ∩ 𝐡𝐡 = {44 π‘€π‘€β„Žπ‘€π‘€ π‘Ÿπ‘Ÿπ‘’π‘’π‘›π‘›π‘Ÿπ‘Ÿπ‘’π‘’π‘€π‘€ π‘π‘π‘€π‘€π‘›π‘›π‘‘π‘‘π‘Ÿπ‘Ÿπ‘‘π‘‘π‘’π‘’π‘’π‘’ π‘Ÿπ‘Ÿπ‘’π‘’π‘€π‘€ 𝑛𝑛𝑛𝑛𝑒𝑒 𝑀𝑀𝑛𝑛𝑛𝑛𝑑𝑑𝑛𝑛}. Then

𝑃𝑃(𝐴𝐴 βˆͺ 𝐡𝐡) = 𝑃𝑃(𝐴𝐴) + 𝑃𝑃(𝐡𝐡)βˆ’ 𝑃𝑃(𝐴𝐴 ∩ 𝐡𝐡) = 134 1,000

+ 50 1,000

βˆ’ 44 1,000

= 140 1,000

= 0.140

Disjoint Events

The events 𝐴𝐴 and 𝐡𝐡 are said to be disjoint (or mutually exclusive) if they have no outcomes in common and therefore cannot occur simultaneously. In other words, 𝐴𝐴 ∩ 𝐡𝐡 = βˆ…. If A and B are disjoint, then 𝑃𝑃(𝐴𝐴 ∩ 𝐡𝐡) = 0, and

𝑃𝑃(𝐴𝐴 βˆͺ 𝐡𝐡) = 𝑃𝑃(𝐴𝐴) + 𝑃𝑃(𝐡𝐡) Example 6: Suppose we draw a single card from a standard 52-card poker deck. What is the probability that the card is either a face card or a “5”? (Refer to the “Resources” page in the “Start Here” module for a link with more information on card decks.)

Define 𝐴𝐴 = {12 π‘‘π‘‘π‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘’π‘’ π‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘›π‘›π‘€π‘€π‘›π‘›}, 𝐡𝐡 = {4 “𝑑𝑑𝑑𝑑𝑒𝑒𝑒𝑒” π‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿπ‘›π‘›π‘€π‘€π‘›π‘› }. A card can’t be both A face card and a “five,” so 𝐴𝐴 ∩ 𝐡𝐡 = βˆ…. Then

𝑃𝑃(𝐴𝐴 βˆͺ 𝐡𝐡) = 𝑃𝑃(𝐴𝐴) + 𝑃𝑃(𝐡𝐡) = 12 52

+ 4 52

= 16 52

= 4 13

= 0.308

Example 7: In a certain lottery, winning numbers are determined by selecting from a set of 10 plastic balls numbered 0 through 9. If a single ball is selected at random, what is the probability of selecting either an even- numbered ball or the ball marked “3”? (Note: assume 0 is even.)

Define 𝐴𝐴 = {0, 2, 4, 6, 8}, 𝐡𝐡 = {3}. A ball can’t display a number that is both even and a 3, so 𝐴𝐴 ∩ 𝐡𝐡 = βˆ…. Then

𝑃𝑃(𝐴𝐴 βˆͺ 𝐡𝐡) = 𝑃𝑃(𝐴𝐴) + 𝑃𝑃(𝐡𝐡) = 5 10

+ 1 10

= 6 10

= 3 5

= 0.600

Complementary Events

The complement of event A is the subset of all outcomes in 𝑆𝑆 that are not in 𝐴𝐴. There is no standard notation for the complement of a subset; we will use 𝐴𝐴𝐢𝐢 to stay consistent with the (optional) textbook.

For any properly constructed experiment, an individual outcome cannot be in both 𝐴𝐴 and 𝐴𝐴𝐢𝐢. In other words, 𝐴𝐴 and 𝐴𝐴𝐢𝐢 are disjoint, and since they contain all the outcomes in 𝑆𝑆 between them, it follows that 𝐴𝐴 βˆͺ 𝐴𝐴𝐢𝐢 = 𝑆𝑆, and further that

𝑃𝑃(𝐴𝐴) + 𝑃𝑃(𝐴𝐴𝐢𝐢) = 1

This equation can also be written in one of the following two equivalent forms:

𝑃𝑃(𝐴𝐴) = 1 βˆ’ 𝑃𝑃(𝐴𝐴𝐢𝐢)

𝑃𝑃(𝐴𝐴𝐢𝐢) = 1 βˆ’ 𝑃𝑃(𝐴𝐴) Example 8: Suppose we draw a single card from a standard 52-card poker deck (assume a “2” is the lowest card and an ace is the highest). What is the probability of drawing a “5” or higher?

If we define 𝐴𝐴 = {“𝑑𝑑𝑑𝑑𝑒𝑒𝑒𝑒” 𝑀𝑀𝑛𝑛 β„Žπ‘‘π‘‘π‘‘π‘‘β„Žπ‘’π‘’π‘›π‘›}, then 𝐴𝐴𝐢𝐢 = {2, 3, 4 𝑀𝑀𝑑𝑑 π‘’π‘’π‘Ÿπ‘Ÿπ‘Ÿπ‘Ÿβ„Ž π‘›π‘›π‘›π‘›π‘‘π‘‘π‘Ÿπ‘Ÿ} (note that 𝐴𝐴𝐢𝐢 has 12 total elementsβ€”three cards Γ— four suits). Then

𝑃𝑃(𝐴𝐴) = 1 βˆ’ 𝑃𝑃(𝐴𝐴𝐢𝐢) = 1 βˆ’ 12 52

= 40 52

= 10 13

= 0.769.

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