BUSN311 Discrete Probability Distribution Discussion
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BUSN311 Discrete Probability Distribution Discussion
My BUSN311 U2 was incorrect, please template with the figures
Assignment 2
Title:
Unit2 – intellipath
Type:
Deliverable Length:
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Due Date:
6/23/2014
Possible Points:
120
Description:
Unit 2:
Unit 2
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Grading Criteria:
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Measurable Terminal Course Objectives:
There are no TCOs for this Learning Event.
Feature List:
Learning Materials
Live Session Talking Points:
Event
Defined
Outcome of a probability experiment
Sample Space
Collection of all events
List of all possible outcomes
Properties of Probability
Individual Probabilities
Each individual probability must be between 0 and 1 inclusive
Sum of Probabilities
The entire sample space of probabilities must always sum to 1
Classical Probability
Requires equally likely outcomes
Each event’s probability is the same
Number of ways event can occur/ Number of possible outcomes
No probability experiment is performed
“TRUE” probability
Empirical Probability
Probability experiment is performed
Frequency of event / number of trials of experiment
Estimated value as each probability experiment will produce different results
Rules
Complement
Probability the event did not happen
One minus the probability event did happen
Addition Rule
“OR” probability of multiple events
Multiplication Rule
“AND” probability of multiple events
Conditional Probability
Given information ahead of time
Information can change the probability results
Uses | as given sign
Used with dependent events
Random Variables
Variable: used to represent a value associated with a probability outcome
Types
Discrete
Countable with distinct separation between each
Continuous
Infinite or with upper bounds that take on a range of values
Discrete Probability Distribution
Distribution
Measurement of probability data set
Consist of probability values between zero and one, inclusive
Probabilities must add to one
Binomial vs. Poisson
Both discrete probability distributions
Binomial
Two possible outcomes
Find number of successes in a fixed number of trials
Poisson
Interval probability
Find probability occurred in a particular interval of time
Expectation
Expected Value
Experiment ran over and over
In the long run what would be expected
Multiply each value of random variable by particular probability and sum
Normal Distribution
Continuous Random Variable
Symmetrical
Mean, Median, Mode all equal
Standardized data for Normal table lookup
Mean = 0
Standard Deviation = 1
Unit Resources:
Common Probability Distributions
How To Use Excel to Make a Frequency Table
Univ. of Calif. -TDIST, TINV, NORMSDIST and NORMSINV
Deakin University – Deakin Business School – Probability & Stats.
Engineering Statistics Handbook
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