Introduction to Probability Ginger Holmes Rowell, Middle TN State University MSP Workshop June 2007.
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Transcript of Introduction to Probability Ginger Holmes Rowell, Middle TN State University MSP Workshop June 2007.
Introduction to Introduction to ProbabilityProbability
Ginger Holmes Rowell, Ginger Holmes Rowell, Middle TN State UniversityMiddle TN State University
MSP WorkshopMSP WorkshopJune 2007June 2007
ObjectivesObjectives• Understand the concepts ofUnderstand the concepts of
• sample space and probability distribution and sample space and probability distribution and construct sample spaces and distributions in simple construct sample spaces and distributions in simple casescases
• conditional probability and independent events; conditional probability and independent events; understand how to compute the probability of a understand how to compute the probability of a compound eventcompound event
• Use simulations to construct empirical probability Use simulations to construct empirical probability distributions and to make informal inferences about the distributions and to make informal inferences about the theoretical probability distribution theoretical probability distribution
Probability ReviewProbability Review
• DefinitionsDefinitions
• Classical ProbabilityClassical Probability
• Relative Frequency ProbabilityRelative Frequency Probability
• Probability Fundamentals andProbability Fundamentals and Probability Rules Probability Rules
What is Probability?What is Probability?
• ProbabilityProbability the study of chance associated the study of chance associated
with the occurrence of eventswith the occurrence of events
• Types of ProbabilityTypes of Probability• Classical (Theoretical)Classical (Theoretical)• Relative Frequency (Experimental)Relative Frequency (Experimental)
Classical ProbabilityClassical Probability
Rolling dice and tossing a coin are Rolling dice and tossing a coin are activities associated with a activities associated with a classical approach to probability. classical approach to probability. In these cases, you can list all the In these cases, you can list all the possible outcomes of an possible outcomes of an experiment and determine the experiment and determine the actual probabilities of each actual probabilities of each outcome. outcome.
Listing Listing All Possible OutcomesAll Possible Outcomes of a Probabilistic Experiment of a Probabilistic Experiment
• There are various ways to list all There are various ways to list all possible outcomes of an possible outcomes of an experiment experiment • EnumerationEnumeration• Tree diagramsTree diagrams• Additional methods – counting Additional methods – counting
fundamentalsfundamentals
Three Children ExampleThree Children Example
• A couple wants to have exactly 3 A couple wants to have exactly 3 children. Assume that each children. Assume that each child is either a boy or a girl and child is either a boy or a girl and that each is a single birth. that each is a single birth.
• List all possible orderings for List all possible orderings for the 3 children.the 3 children.
EnumerationEnumeration11stst Child Child 22ndnd Child Child 33rdrd Child Child
BB BB BB
GG BB BB
BB GG BB
BB BB GG
GG GG BB
GG BB GG
BB GG GG
GG GG GG
Tree DiagramsTree Diagrams
1st Child 2nd Child 3rd Child BBBBBB
BB
G
B
GB
G
BBGBBGBGBBGBBGGBGGGBBGBBGBGGBGGGBGGBGGGGGG
GB
G
B
GB
G
DefinitionsDefinitions
• Sample SpaceSample Space - the list of all - the list of all possible outcomes from a possible outcomes from a probabilistic experiment. probabilistic experiment. • 3-Children Example:3-Children Example:
S = {BBB, BBG, BGB, BGG, S = {BBB, BBG, BGB, BGG, GBB, GBG, GGB, GGG} GBB, GBG, GGB, GGG}
• Each individual item in the list is called Each individual item in the list is called a a Simple EventSimple Event or or Single Event.Single Event.
Probability NotationProbability Notation
P(P(eventevent) = Probability of the ) = Probability of the eventevent occurringoccurring
Example: P(Boy) = P(B) = ½Example: P(Boy) = P(B) = ½
Probability of Single Events Probability of Single Events with Equally Likely Outcomeswith Equally Likely Outcomes
• If each outcome in the sample space If each outcome in the sample space is is equally likelyequally likely, then , then the probability of the probability of any one outcome is 1 divided by the any one outcome is 1 divided by the total number of outcomestotal number of outcomes..
outcomes ofnumber total
1event) simple(
outcomes,likely equally For
P
Three Children Example Three Children Example ContinuedContinued
• A couple wants 3 children. A couple wants 3 children. Assume the chance of a boy or Assume the chance of a boy or girl is girl is equally likelyequally likely at each birth. at each birth.
• What is the What is the probabilityprobability that they that they will have will have exactly 3 girlsexactly 3 girls? ?
• What is the What is the probabilityprobability of ofhaving having exactly 3 boysexactly 3 boys??
Probability of Combinations of Probability of Combinations of Single EventsSingle Events
• An An EventEvent can be a combination can be a combination of of Single EventsSingle Events..
• The probability of such an event The probability of such an event is the sum of the individual is the sum of the individual probabilities.probabilities.
Three Children Example Three Children Example ContinuedContinued
P(exactly 2 girls) = __P(exactly 2 girls) = __
P(exactly 2 boys) = __P(exactly 2 boys) = __
P(at least 2 boys) = __P(at least 2 boys) = __
P(at most 2 boys) = __P(at most 2 boys) = __
P(at least 1 girl) = __P(at least 1 girl) = __
P(at most 1 girl) = __P(at most 1 girl) = __
• Sample Sample space =space =
Types of ProbabilityTypes of Probability
• Classical (Theoretical)Classical (Theoretical)
• Relative Frequency Relative Frequency (Experimental, Empirical)(Experimental, Empirical)
Relative Frequency ProbabilityRelative Frequency Probability
• Uses actual experience to Uses actual experience to determine the likelihood of an determine the likelihood of an outcome.outcome.
• What isWhat isthe chancethe chanceof makingof makinga B or better?a B or better?
GradeGrade FrequencyFrequency
AA 2020
BB 3030
CC 4040
Below CBelow C 1010
Relative Frequency Probability Relative Frequency Probability is Great Fun for Teachingis Great Fun for Teaching
• Rolling DiceRolling Dice
• Flipping CoinsFlipping Coins
• Drawing from Bags without Looking Drawing from Bags without Looking (i.e. Sampling)(i.e. Sampling)
• Sampling with M&M's Sampling with M&M's ((http://mms.com/cai/mms/faq.html#whhttp://mms.com/cai/mms/faq.html#what_percentat_percent))
Empirical ProbabilityEmpirical Probability
• Given a frequency distribution, Given a frequency distribution, the probability of an event, E, the probability of an event, E, being in a given group isbeing in a given group is
n
xP
ondistributi in the sfrequencie total
group theoffrequency E)(
Two-way Tables and Two-way Tables and ProbabilityProbability
• FindFind
P(M) P(M)
P(A)P(A)
P(A and M)P(A and M)
Made Made AA
Made Made
< A< ATotalTotal
MaleMale 3030 4545
FemaleFemale 6060 6565
TotalTotal
Teaching IdeaTeaching Idea
• Question: How Can You Win at Question: How Can You Win at Wheel of Fortune?Wheel of Fortune?
• Answer: Use Relative Frequency Answer: Use Relative Frequency Probability (see handout)Probability (see handout)
Source. Krulik and Rudnick. “Teaching Middle School Mathematics Activities, Materials and Problems.” p. 161. Allyn & Bacon, Boston. 2000.
Probability FundamentalsProbability Fundamentals
• What is What is wrongwrong with the statements? with the statements?• The probability of rain today is -10%.The probability of rain today is -10%.• The probability of rain today is 120%.The probability of rain today is 120%.• The probability of rain or no rain today is The probability of rain or no rain today is
90%.90%.
1) (
1)(
0)(
spacesampleP
eventP
eventP
Probability RulesProbability Rules
Let A and B be eventsLet A and B be events
Complement Rule:Complement Rule:
P(A) + P(not A) = 1P(A) + P(not A) = 1
Set NotationSet Notation
Union: A or B Union: A or B (inclusive “or”)(inclusive “or”)
BA
BA
Intersection: A and BIntersection: A and B
Probability RulesProbability Rules
Union P(AUB) = P(A or B)Union P(AUB) = P(A or B)
)()()()( BAPBPAPBAP
• Venn DiagramsVenn Diagrams
• Kyle Siegrist’s Venn Diagram Kyle Siegrist’s Venn Diagram AppletApplet
http://www.math.uah.edu/stat/applhttp://www.math.uah.edu/stat/applets/index.xmlets/index.xml
Teaching IdeaTeaching Idea
Two-way Tables and Two-way Tables and ProbabilityProbability
• FindFind
P(M)P(M)
P(A)P(A)
P(A and M)P(A and M)
P(A if M)P(A if M)
Made Made AA
Made Made
< A< A
TotalTotal
MaleMale 3030 4545 7575
FemaleFemale 6060 6565 125125
TotalTotal 9090 110110 200200
Conditional ProbabilityConditional Probability
P(A|B) = the conditional P(A|B) = the conditional probability of event A happening probability of event A happening given that event B has happenedgiven that event B has happened
“ “probability of A given B”probability of A given B”
)(
)()|(
BP
BAPBAP
IndependenceIndependence
• Events A and B are Events A and B are “Independent” if and only if“Independent” if and only if
)()|( APBAP
• Using the data in the two-way Using the data in the two-way table, is making an “A” table, is making an “A” independent from being male? independent from being male?