'2 statistic' diaporamas de présentation

Statistical Data Analysis Stat 3: p -values, parameter estimation

Statistical Data Analysis Stat 3: p -values, parameter estimation. London Postgraduate Lectures on Particle Physics; University of London MSci course PH4515. Glen Cowan Physics Department Royal Holloway, University of London g.cowan@rhul.ac.uk www.pp.rhul.ac.uk/~cowan. Course web page:

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Testing Goodness-of-Fit for a Single Categorical Variable

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Test of Goodness of Fit

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Lesson 14 - 2

Lesson 14 - 2. Inference for Two-Way Tables. Knowledge Objectives. Explain what is mean by a two-way table . Define the chi-square (? 2 ) statistic . Identify the form of the null hypothesis in a ? 2 test for homogeneity of populations .

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Crosstabulation

Crosstabulation. Measuring Association To what extent are two variables, X and Y , related? Begin with the idea of statistical independence. Room Temperature Mean Exam Score 72 75 85 75 98 75.

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Multinomial Experiments Goodness of Fit Tests

Multinomial Experiments Goodness of Fit Tests. We have just seen an example of comparing two proportions. For that analysis, we used the normal distribution as a sampling distribution.

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A taste of statistics

A taste of statistics. Normal error (Gaussian) distribution ? most important in statistical analysis of data, describes the distribution of random observations for many experiments Poisson distribution ? generally appropriate for counting experiments related to

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Lecture 11. The chi-square test for goodness of fit

Lecture 11. The chi-square test for goodness of fit. Objectives. The chi-square test for goodness of fit (Single Award) Idea of the chi-square test The chi-square distributions Goodness of fit hypotheses Conditions for the chi-square goodness of fit test Chi-square test for goodness of fit.

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Chapter 22

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STAT 3120 Statistical Methods I

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What Types Of Data Are Collected?

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Paper By: Yiming Yang, CMU Jan O. Pedersen, Verity, Inc. Presented By: Prerak Sanghvi

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Tests For Multinomials

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A.P. STATISTICS LESSON 13 -1 (DAY 1)

A.P. STATISTICS LESSON 13 -1 (DAY 1). CONDUCTING INFERENCE BY SIMULATION. ESSENTIIAL QUESTION: How can the graphing calculator be used to simulate problems involving chi-square ?. Objectives: To set up simulations to solve problems. To use the calculator to find P-values for chi-square.

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A.P. STATISTICS LESSON 13 -1 (DAY 1)

A.P. STATISTICS LESSON 13 -1 (DAY 1). CONDUCTING INFERENCE BY SIMULATION. ESSENTIIAL QUESTION: How can the graphing calculator be used to simulate problems involving chi-square ?. Objectives: To set up simulations to solve problems. To use the calculator to find P-values for chi-square.

121 views • 6 slides