IE 300, Fall 2012 Richard Sowers IESE. 8/30/2012 Goals: Rules of Probability Counting Equally likely...
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Transcript of IE 300, Fall 2012 Richard Sowers IESE. 8/30/2012 Goals: Rules of Probability Counting Equally likely...
![Page 1: IE 300, Fall 2012 Richard Sowers IESE. 8/30/2012 Goals: Rules of Probability Counting Equally likely Some examples.](https://reader036.fdocuments.in/reader036/viewer/2022062423/5697bfa41a28abf838c97358/html5/thumbnails/1.jpg)
IE 300, Fall 2012Richard Sowers
IESE
![Page 2: IE 300, Fall 2012 Richard Sowers IESE. 8/30/2012 Goals: Rules of Probability Counting Equally likely Some examples.](https://reader036.fdocuments.in/reader036/viewer/2022062423/5697bfa41a28abf838c97358/html5/thumbnails/2.jpg)
8/30/2012
Goals:•Rules of Probability•Counting•Equally likely•Some examples
![Page 3: IE 300, Fall 2012 Richard Sowers IESE. 8/30/2012 Goals: Rules of Probability Counting Equally likely Some examples.](https://reader036.fdocuments.in/reader036/viewer/2022062423/5697bfa41a28abf838c97358/html5/thumbnails/3.jpg)
9/4/2012
Goals•Conditional Probability•Model-building
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9/6/2012
• Independence– Definition– Model-building– Examples
![Page 5: IE 300, Fall 2012 Richard Sowers IESE. 8/30/2012 Goals: Rules of Probability Counting Equally likely Some examples.](https://reader036.fdocuments.in/reader036/viewer/2022062423/5697bfa41a28abf838c97358/html5/thumbnails/5.jpg)
9/11/2012
• Bayes’ Rule– Implicit conditional probabilities
• Random variables (if possible)
![Page 6: IE 300, Fall 2012 Richard Sowers IESE. 8/30/2012 Goals: Rules of Probability Counting Equally likely Some examples.](https://reader036.fdocuments.in/reader036/viewer/2022062423/5697bfa41a28abf838c97358/html5/thumbnails/6.jpg)
9/13/2012
• Discrete random variables– Examples
• Uniform• Geometric• Binomial• Bernoulli
– Probability mass functions• Expectations
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9/27/2012
• Expectations and variances– Direct computations– Moment generating functions (not in book)
![Page 8: IE 300, Fall 2012 Richard Sowers IESE. 8/30/2012 Goals: Rules of Probability Counting Equally likely Some examples.](https://reader036.fdocuments.in/reader036/viewer/2022062423/5697bfa41a28abf838c97358/html5/thumbnails/8.jpg)
9/18/2012
• Expectations– Means– Variances– Moment generating functions
• Several random variables– Binomial– Geometric– Bernoulli– Poisson– Uniform
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9/20/2012
• Review
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9/28/2012
• Expectations and Variances– Bernoulli– Binomial– Law of large numbers
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10/2/2012
• Moment generating function– Bernoulli– Binomial– Geometric– Negative Binomial– Poisson
• Begin continuous random variables
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10/4/2012
• Continuous random variables• Properties of densities• Exponential random variables
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10/9/2012
• Poisson connection to exponential random variables
• Gaussian random variables
![Page 14: IE 300, Fall 2012 Richard Sowers IESE. 8/30/2012 Goals: Rules of Probability Counting Equally likely Some examples.](https://reader036.fdocuments.in/reader036/viewer/2022062423/5697bfa41a28abf838c97358/html5/thumbnails/14.jpg)
10/11/2012
• Gaussian random variables• Limit theorems
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10/18/2012
• Joint random variables• Joint probability mass function• Conditioning• Marginals
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10/23/2012
• More joint random variables• Joint probability mass function• Conditioning• Marginals
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11/1/2012
• More on transformations of random variables
• Joint Gaussians
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11/6/2012
• Statistical analysis of data• Sample mean, sample variance, population
variance• Histograms and frequency plots
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11/13/2012
• Estimation of parameters– Bernoulli– Exponential– Gaussian
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11/15/2012
• Hypothesis testing (9-5)