Chap 4-1
Business Statistics: A Decision-Making Approach
7th Edition
Chapter 4Using Probability and
Probability Distributions
4-2
Important Terms Random Variable - Represents a possible numerical value
from a random event and it can vary from trial to trial Probability – the chance that an uncertain event will occur Experiment – a process that produces outcomes for
uncertain events Sample Space (or event) – the collection of all possible
experimental outcomes
4-3
Basic Rule of Probability
Individual Values Sum of All Values
0 ≤ P(Ei) ≤ 1
For any event Ei
1)P(ek
1ii
where:k = Number of individual outcomes in the sample spaceei = ith individual outcome
The value of a probability is between 0 and 1
0 = no chance of occurring1 = 100% change of occurring
The sum of the probabilities of all the outcomes in a sample space must = 1 or 100%
Simple probability
The probability of an event is the number of favorable outcomes divided by the total number of possible equally-likely outcomes. This assumes the outcomes are all equally weighted. Textbook: classical probability
Chap 4-4
Chap 4-5
Visualizing Events (or sample space)
Contingency Tables
Tree Diagrams
Red 2 24 26 Black 2 24 26
Total 4 48 52
Ace Not Ace Total
Full Deck of 52 Cards
Red Card
Black Card
Not an Ace
Ace
AceNot an Ace
Sample Space
Sample Space2
24
2
24
Chap 4-6
Experimental Outcome Example A automobile consultant records fuel type and vehicle
type for a sample of vehicles 2 Fuel types: Gasoline, Diesel 3 Vehicle types: Truck, Car, SUV
6 possible experimental outcomes: e1 Gasoline, Truck e2 Gasoline, Car e3 Gasoline, SUV e4 Diesel, Truck e5 Diesel, Car e6 Diesel, SUV
Gasoline
Diesel
CarTruck
Truck
Car
SUV
SUV
e1
e2
e3
e4
e5
e6
Simple probability
What is the probability that a card drawn at random from a deck of cards will be an ace? 52 cards in the deck and 4 are aces The probability is ???? Each card represents a possible outcome 52
possible outcomes.
Chap 4-7
Simple probability
Chap 4-8
There are 36 possible outcomes when a pair of dice is thrown.
Simple probability
Calculate the probability that the sum of the two dice will be equal to 5? Four of the outcomes have a total of 5: (1,4; 2,3;
3,2; 4,1) Probability of the two dice adding up to 5 is ????.
Chap 4-9
Simple probability
Calculate the probability that the sum of the two dice will be equal to 12? Only one (6,6) ????
Chap 4-10
Simple Probability
The probability of event A is denoted by P(A) Example: Suppose a coin is flipped 3 times. What is the
probability of getting two tails and one head? The sample space consists of 8 possible outcomes. S = {TTT, TTH, THT, THH, HTT, HTH, HHT, HHH} the probability of getting any particular outcome is 1/8. Getting two tails and one head: A = {TTH, THT, HTT} P(A) = ????
Chap 4-11
Essential Concepts and Rules of Probability
Independent event Dependent event Joint and Conditional Probabilities Mutually Exclusive Event Addition Rule Complement Rule Multiplication Rule
Chap 4-12
Chap 4-13
Independent: Occurrence of one does not influence the
probability of occurrence of the other
Dependent: Occurrence of one affects the probability of the
other
Independent vs. Dependent Events
Chap 4-14
Independent EventsA = heads on one flip of fair coinB = heads on second flip of same coin
Result of second flip does not depend on the result of the first flip.
Dependent EventsX = rain forecasted on the newsY = take umbrella to work
Probability of the second event is affected by the occurrence of the first event
Examples
Probability Types
Simple (Marginal) probability Involves only a single random variable, the outcome of which is
uncertain Joint probability
Involves two or more random variables, in which the outcome of all is uncertain
Conditional probability (will be discussed soon!) Download “Probability Type Example ” Excel file
Chap 4-15
Exercise 4-22-A (page 158)
Chap 4-16
Download “Computer Use” Answer for questions using “Pivot Table”
Exercise 4-22-B (page 158)
Chap 4-17
Practice
Exercise 4-23: try questions.
Chap 4-18
Electrical Mechanical Total
Lincoln 28 39 67
Tyler 64 69 133
Total 92 108 200
Conditional Probability: ex 1 A conditional probability is the probability of an event
given that another event has occurred. Involves two or more random variables, in which the outcome of
at least one is known Conditional probability for any two events A , B:
Chap 4-19
P(B))andP(AB)|P(A B
0P(B)where
Notation
Chap 4-20
What is the probability that a car has a CD player, given that it has AC (use the table on the next slide)?
i.e., we want to find P(CD | AC)
Conditional Probability: ex 1
Of the cars on a used car lot, 70% have air conditioning (AC) and 40% have a CD player (CD). 20% of the cars have both.
Chap 4-21
Conditional Probability: ex 1
No CDCD TotalAC .2 .5 .7No AC .2 .1 .3Total .4 .6 1.0
What is the probability that a car has a CD player, given that it has AC ?
.2857.7.2
P(AC)AC)andP(CDAC)|P(CD
Conditional Probability: ex 2
What is the probability that the total of two dice will be greater than 8 given that the first die is a 6? This can be computed by considering only outcomes
for which the first die is a 6. Then, determine the proportion of these outcomes that total more than 8.
Chap 4-22
Conditional Probability: ex 2
There are 6 outcomes for which the first die is a 6.
And of these, there are four that total more than 8.
(6,3; 6,4; 6,5; 6,6)
Chap 4-23
Conditional Probability: ex 2
6 outcomes for which the first die is a 6 There are four that total more than 8 The probability of a total greater than 8 given that the
first die is 6 is 4/6 = 2/3. More formally, this probability can be written as:
p(total>8 | Die 1 = 6) = 2/3(6,3; 6,4; 6,5; 6,6). Conditional probability using “Probability Type
Example” Excel file
Chap 4-24
Chap 4-25
Mutually Exclusive Events
If A occurs, then B cannot occur A and B have no common elements
Black Cards
Red Cards
A card cannot be Black and Red at the same time.
AB
Mutually Exclusive Events
If events A and B are mutually exclusive, then the probability of A or B is p(A or B) = p(A) + p(B)
What is the probability of rolling a die and getting either a 1 or a 6?
impossible to get both a 1 and a 6 p(1 or 6) = p(1) + p(6) = 1/6 + 1/6 = 1/3
Chap 4-26
Chap 4-27
Not Mutually Exclusive Events
P(A or B) = P(A)+ P(B) – P(A and B)
A B
P(A or B) = P(A) + P(B) - P(A and B)Overlap: joint probability
■ If the events are not mutually exclusive,
A B+ =
Not Mutually Exclusive Events
What is the probability that a card will be either an ace or a spade?
p(ace) = 4/52 and p(spade) = 13/52 The only way both can be drawn is to draw the ace of
spades. There is only one ace of spades: p(ace and spade) = 1/52 .
The probability of an ace or a spade can be: p(ace) + p(spade) - p(ace and spade) = 4/52 + 13/52 - 1/52 = 16/52 = 4/13
Chap 4-28
Rule of Addition
Suppose we have two events and want to know the probability that either event occurs.
Mutually exclusive: P(A or B) = P(A) + P(B)
Not Mutually exclusive: P(A or B) = P(A)+ P(B) – P(A and B)
Chap 4-29
Chap 4-30
Complement Rule
The complement of an event E is the collection of all possible elementary events not contained in event E. The complement of event E is represented by E.
Complement Rule:
)EP(1P(E)
E
E1)EP(P(E)
Or,
If there is a 40% ( E ) chance it will rain,
there is a 60% ( E ) chance it won’t rain!
Rule of Multiplication
The rule of multiplication applies to the situation when we want to know the probability that both events (event A and event B) occur. Addition: either events
Independent: P(A ∩ B) = P(A) P(B) Dependent: P(A ∩ B) = P(A) P(B|A)
Chap 4-31
Independent Events
If A and B are independent, then the probability that events A and B both occur is: p(A and B) = p(A) x p(B)
What is the probability that a coin will come up with heads twice in a row?
Two events must occur: a head on the first toss and a head on the second toss.
The probability of each event is 1/2 the probability of both events is: 1/2 x 1/2 = 1/4.
Chap 4-32
Independent Events
What is the probability that the first card is the ace of clubs (put it back: replace) and the second card is a club (any club)? The probability of the first event is 1/52 (only one ace
of club) The probability of the second event is 13/52 = 1/4
(composed of clubs) Answer is 1/52 x 1/4 = 1/208
Chap 4-33
Dependent Events
If A and B are not independent, then the probability of A and B both occur is:
p(A and B) = p(A) x p(B|A) where p(B|A) is the conditional probability of B given A.
Chap 4-34
Dependent Events
If someone draws a card at random from a deck and then, without replacing the first card, draws a second card, what is the probability that both cards will be aces?
4 of the 52 cards are aces First: p(A) = 4/52 = 1/13.
Of the 51 remaining cards, 3 are aces. So, p(B|A) = 3/51 = 1/17
Probability of A and B is: 1/13 x 1/17 = 1/221.
Chap 4-35
Practice
Page 180 Exercise 4-26 Exercise 4-30
Chap 4-36
Summary
Probability Rules Addition Rule for Two Events Addition Rule for Mutually Exclusive Events Conditional Probability Multiplication Rules
Chap 4-37