Chapter 2
Introduction to Probability
Learning Objectives
1. Obtain an understanding of the role probability information plays in the decision making process.
2. Understand probability as a numerical measure
...
Chapter 2
Introduction to Probability
Learning Objectives
1. Obtain an understanding of the role probability information plays in the decision making process.
2. Understand probability as a numerical measure of the likelihood of occurrence.
3. Be able to use the three methods (classical, relative frequency, and subjective) commonly used for assigning probabilities and understand when they should be used.
4. Be able to use the addition law and be able to compute the probabilities of events using conditional probability and the multiplication law.
5. Be able to use new information to revise initial (prior) probability estimates using Bayes' theorem.
6. Know the definition of the following terms:
experiment addition law
sample space mutually exclusive
event conditional probability
complement independent events
Venn Diagram multiplication law
union of events prior probability
intersection of events posterior probability
Bayes' theorem Simpson’s Paradox
Solutions:
1. a. Go to the x-ray department at 9:00 a.m. and record the number of persons waiting.
b. The experimental outcomes (sample points) are the number of people waiting: 0, 1, 2, 3, and 4.
Note: While it is theoretically possible for more than 4 people to be waiting, we use what has actually been observed to define the experimental outcomes.
c.
Number Waiting Probability
0 .10
1 .25
2 .30
3 .20
4 .15
Total: 1.00
d. The relative frequency method was used.
2. a. Choose a person at random, have her/ him taste the 4 blends and state a preference.
b. Assign a probability of 1/4 to each blend. We use the classical method of equally likely outcomes here.
c.
Blend Probability
1 .20
2 .30
3 .35
4 .15
Total: 1.00
The relative frequency method was used.
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