'Independent trials' presentation slideshows

Last Time

Last Time. Administrative Matters – Blackboard … Random Variables Abstract concept Probability distribution Function Summarizes probability structure Sum to get any prob. Binomial Distribution. Reading In Textbook. Approximate Reading for Today’s Material:

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Chapter 7 The Normal Probability Distribution

Chapter 7 The Normal Probability Distribution. 7.5 Sampling Distributions; The Central Limit Theorem. Illustrating Sampling Distributions Step 1: Obtain a simple random sample of size n . Illustrating Sampling Distributions Step 1: Obtain a simple random sample of size n .

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Lesson 8 - R

Lesson 8 - R. Review of Chapter 8 Discrete PDFs Binomial and Geometeric. Objectives. Explain what is meant by a binomial setting and binomial distribution. Use technology to solve probability questions in a binomial setting.

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Lesson 8 - R

Lesson 8 - R. Review of Chapter 8 Discrete PDFs Binomial and Geometeric. Objectives. Explain what is meant by a binomial setting and binomial distribution. Use technology to solve probability questions in a binomial setting.

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I. Randomness

I. Randomness. Random (def.): Proceeding, made, or occurring without definite aim, reason or pattern. (OED) Randomness can have structure and, if so, we can use that structure to make predictions about subsequent outcomes.

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Categorical Data

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Chapter 8 Review: The Binomial and Geometric Distributions

Chapter 8 Review: The Binomial and Geometric Distributions. Kate Schwartz & Lexy Ellingwood. The Big Idea.

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Chapter Five

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7.3 Binomial Trials

7.3 Binomial Trials . Binomial Trials: Success/Failure Probability of k Successes. Binomial Trials: Success/Failure. An experiment with just 2 outcomes is called a binomial trial (or Bernoulli trial. ) One outcome is labeled a success and the other is labeled a failure.

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STAT 135 LAB 10

STAT 135 LAB 10. Learning Objective # 67 TA: Dongmei Li. A Story.

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The Binomial Distribution

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Figure 1a. Average number of eggs laid by female bean beetles (with and without access to water) on mung beans . A total of 6 independent trials were performed in 2010. .

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The strong law of large numbers

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Errors in Error Variance Prediction and Ensemble Post-Processing Elizabeth Satterfield 1 , Craig Bishop 2

Errors in Error Variance Prediction and Ensemble Post-Processing Elizabeth Satterfield 1 , Craig Bishop 2 1 National Research Council, Monterey, CA, USA; 2 Naval Research Laboratory, Monterey CA, USA. Weather Roulette (Hagedorn and Smith, 2008)

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Chapter 4

Chapter 4. Discrete Random Variables Chapter 4 Objectives. Chapter 4 Objectives. The student will be able to Recognize and understand discrete probability distribution functions, in general. Recognize the Binomial probability distribution and apply it appropriately.

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