Experimental Probability and Simulation
A simulation imitates a real situation Is supposed to give similar resultsAnd so acts as a predictor of what should
actually happen It is a model in which repeated
experiments are carried out for the purpose of estimating in real life
Simulation
Used to solve problems using experiments when it is difficult to calculate theoretically
Often involves either the calculation of:◦ The long-run relative frequency of an event happening◦ The average number of ‘visits’ taken to a ‘full-set’
Often have to make assumptions about situations being simulated. E.g. there is an equal chance of producing a boy or a girl
Maths online
Simulating tossing a fair coin
AC/on RUN <Exe> OPTN F6 PROB Ran#
Random Numbers on Casio fx-9750G PLUS
1. To Simulate tossing of a coin◦ Ran#
Heads: 0.000 000 -0.499 999 Tails: 0.500 000 – 0.999 999
2. To simulate LOTTO balls◦ 1+40Ran#, truncate the result to 0 d.p., or◦ 0.5+40Ran#, truncate the result to 0 d.p.
Random Numbers (some ideas)
3. To simulate an event which has 14% chance of success
◦ 100Ran#, truncate the result to 0 d.p. 0 – 13 for success, 14-99 for failure, or
◦ 1+100Ran#, truncate the result to 0 d.p. 1-14 for success, 15-100 for failure
Random Numbers
Assume each day has equal probability (1/7)
Use spreadsheet function RANDBETWEEN(1,7)
Generate 4 random numbers to simulate one family
Repeat large number of times
Eg: Simulate probability that 4 members of a family were each born on a different day
Day of the week
Random Number
Sunday 1
Monday 2
Tuesday 3
Wednesday
4
Thursday 5
Friday 6
Saturday 7
Microsoft Office Excel Chart
The description of a simulation should contain at least the following four aspects:
Tools Definition of the probability tool, eg. Ran#, Coin, deck of
cards, spinner Statement of how the tool models the situation
Trials Definition of a trial Definition of a successful outcome of the trial
Results Statement of how the results will be tabulated giving an
example of a successful outcome and an unsuccessful outcome
Statements of how many trials should be carried out
TTRC
TTRC continued
Calculations
Statement of how the calculation needed for the conclusion will be done
Long-run relative frequency =
Mean =
trialsofNumber
results ’successful‘ ofNumber
trialsofNumber
results ’successful‘ ofNumber
Problem: What is the probability that a 4-child family will contain exactly 2 boys and 2 girls?
Tool: First digit using calculator 1+10Ran#Odd Numbers stands for ‘Boy’ andEven Number stands for ‘Girl’
Trial: One trial will consist of generating 4 random numbers to
simulate one family.A Successful trial will have 2 odd and 2 even numbers.
Results:
Number of Trials needed: 30 would be sufficientCalculation:
Probability of 2 boys & 2 girls =
Trial Outcome of trial
Result of trial
1 2357 Unsuccessful
2 4635 Successful
trialsofNumber
results ’successful‘ ofNumber
Problem: As a part of Christmas advertising a petrol station gives away one of 6 Lego toys to each customer who purchases $20 or more of fuel.
Calculate how many visits to the petrol station a customer would need to make on average to collect all 6 Lego toys.
Assumption: The likelihood of one Lego toy being handed out is independent of another.
Tool: Generate random numbers between 1 & 6 (inclusive), each number stands for each toy.
Trial: One trial will consist of generating random numbers till all numbers from 1 to 6 have been generated.Count the number of random numbers need to get one full set
Results:
Number of Trials needed: 30 would be sufficient
Calculation:
Average number of visits = Total visitsNumber of trials
Solution (suggestion)
Trial Toy1
Toy2 Toy3 Toy4 Toy5 Toy6 Tally Total Visits
1 Y Y Y Y Y Y 10
2 Y Y Y Y Y Y 19
Problem: Mary has not studied for her Biology test. She does not know any of the answers on a three-question true-false test, and she decides to guess on all three questions
Design a simulation to estimate the probability that Mary will ‘Pass’ the test. (i.e. guess correct answers to atleast 2 of the 3 questions)
Calculate the theoretical probability that Mary will pass the test.
Tool: The probability that Mary guesses a question true is one half.First digit using calculator 1 + 10Ran#1to 5 stands for ‘correct answer’6 to 10 stands for ‘incorrect answer’
Trial: One trial will consist of generating 3 random numbers to simulate Mary answering one complete test.
A successful outcome will be getting atleast 2 of the 3 random numbers between 1 and 5.
Results:
Number of Trials needed: 30 would be sufficientCalculation: Estimate of probability of ‘passing’ the exam =
Solution (suggestion)
Trial Outcome of Trial Result of Trial
1 122 Successful trial
2 167 Unsuccessful trial
trialsofNumber
results ’successful‘ ofNumber
Problem: Mary has not studied for her history test. She does not know any of the answers on an eight-question true-false test, and she decides to guess on all eight questions
Design a simulation to estimate the probability that Mary will ‘Pass’ the test. (i.e. guess correct answers to atleast 4 of the eight questions)
Tool: The probability that Mary guesses a question true is one half.
First digit using calculator 1 + 10Ran#
1to 5 stands for ‘correct answer’
6 to 10 stands for ‘incorrect answer’
Trial: One trial will consist of generating 8 random numbers to simulate Mary answering one complete test.
A successful outcome will be getting atleast 4 of the 8 random numbers between 1 and 5.
Results:
Number of Trials needed: 30 would be sufficient
Calculation:
Estimate of probability of ‘passing’ the exam =
Solution (suggestion)
Trial Outcome of Trial Result of Trial
1 12236754 Successful trial
2 13672987 Unsuccessful trial
trialsofNumber
results ’successful‘ ofNumber
Problem: Lotto 40 balls and to win you must select 6 in any order. In this mini Lotto, there are only 6 balls and you win when you select 2 numbers out of the 6.
Design and run your own simulation to estimate the probability of winning (i.e. selecting 2 numbers out of the 6)Calculate the theoretical probability of winning.
Tool: Two numbers (between 1 and 6) will need to be selected first (say 2 & 4)First digit using calculator 1 + 6Ran#, ignore the decimals.
Trial: One trial will consist of generating 2 random numbersDiscard any repeat numbersA successful outcome will be getting 2 of the 6 random numbers
generatedResults:
Number of Trials needed: 50 would be sufficientCalculation:
Estimate of probability of ‘winning’ = Number of ‘successful’ outcomeNumber of trials
Theoretical probability in this case is 1/15
Solution (suggestion)
Trial Outcome of Trial Result of Trial
1 2 4 Successful trial
2 13 Unsuccessful trial
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