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by: Colin Fritz

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# SCO 2550 Week 3/ Chapter 3 Notes SCO 2550

Marketplace > University of Minnesota > Business statistics > SCO 2550 > SCO 2550 Week 3 Chapter 3 Notes
Colin Fritz
U of M

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These notes cover rules of probability.
COURSE
Business Statistics: Data Sources, Presentation, and Analysis
PROF.
Kedong Chen
TYPE
Class Notes
PAGES
2
WORDS
CONCEPTS
SCO, 2550, Probability, Kedong, chen
KARMA
25 ?

## Popular in Business Statistics: Data Sources, Presentation, and Analysis

This 2 page Class Notes was uploaded by Colin Fritz on Sunday September 25, 2016. The Class Notes belongs to SCO 2550 at University of Minnesota taught by Kedong Chen in Fall 2016. Since its upload, it has received 4 views. For similar materials see Business Statistics: Data Sources, Presentation, and Analysis in Business statistics at University of Minnesota.

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Date Created: 09/25/16
SCO 2550 Week 3/Chapter 3 Notes Colin Fritz Probability  The probability will always be between 0 and 1 = 0 ≤ p ≤ 1 i  Also probabilities of all of the sample points will add up to 1 Event – a collection of sample points also a simple event contains only a single sample point while a compound event contains two or more sample points  To find the probability of an event you sum the probabilities of the sample points in the sample space Complement – the complement of an event is that the particular event does not occur  Rule of compliments = P(A) + P(A’) = 1 Mutually Exclusive – Events A and B are mutually exclusive if A∩B contains no sample points Rule for Union of Two Mutually Exclusive Events P(A∩B) = P(A) + P(B) Additive Rule of Probability To calculate sum the probability of events A and B and then subtract the probability of the intersection of events A and B. This is to avoid double counting. P(A ∪ B) = P(A) + P(B) - P(A ∩ B) Conditional Probability Formula  The probability that event A occurs given that event B occurs  Conditional probability is denoted with a vertical line (|) Multiplicative Rule By rearranging the last formula you can find the intersection of two events this is true for two dependent events P(A ∩ B) = P(A) P(B|A)  If the two events are independent then you can use a much simpler formula: P(A ∩ B) = P(A) * P(B)

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