'Restricted model' presentation slideshows

Lecture 5 The Problem of Statistical Inference (Chapters 5 and 8)

Lecture 5 The Problem of Statistical Inference (Chapters 5 and 8). Hypothesis Testing in the Two-Variable Regression Model-- Continued T esting Hypotheses about a Regression Coefficient Test of Significance Approach  Analysis of Variance Approach .

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Module II Lecture 4:F-Tests

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Sufficient statistics. The Poisson and the exponential can be summarized by (n, ).

More Chapter 4. Sufficient statistics. The Poisson and the exponential can be summarized by (n, ). So too can the normal with known variance Consider a statistic S(Y)

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Design of Engineering Experiments - Experiments with Random Factors

Design of Engineering Experiments - Experiments with Random Factors. Text reference, Chapter 13 Previous chapters have considered fixed factors A specific set of factor levels is chosen for the experiment Inference confined to those levels Often quantitative factors are fixed (why?)

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Detecting Statistical Interactions with Additive Groves of Trees

Detecting Statistical Interactions with Additive Groves of Trees. Daria Sorokina, Rich Caruana, Mirek Riedewald, Daniel Fink. Domain Knowledge Questions. Which features are important? What effects do they have on the response variable? Effect visualization techniques

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Factorial Models

Factorial Models. Random Effects Gauge R&R studies (Repeatability and Reproducibility) have been an expanding area of application Mixed Effects Models. One-way Random Effects. The one-way random effects model is quite different from the one-way fixed effects model

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UPA and Restriction for All-Groups and Numeric Exponents

UPA and Restriction for All-Groups and Numeric Exponents. Matthew Fuchs, PhD Westbridge Technology matt@westbridgetech.com Allen Brown, PhD Microsoft. Why Bother?. Numeric Exponents introduced by the W3C XML Schema WG. Restriction is a subsumption relation among content models.

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Multiple Regression Analysis

Multiple Regression Analysis. y = b 0 + b 1 x 1 + b 2 x 2 + . . . b k x k + u Heteroskedasticity. What is Heteroskedasticity. Recall the assumption of homoskedasticity implied that conditional on the explanatory variables, the variance of the unobserved error, u , was constant

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Introduction to Statistics: Political Science (Class 3)

Introduction to Statistics: Political Science (Class 3). Calculating R-Squared, Dichotomous and Nominal Variables, F-tests. R-Squared. Coef. St.Err T P Bush FT -.090 .489 -0.18 0.860 Party Identification 12.31 7.47 1.65 0.143

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Introduction to Statistics: Political Science (Class 3)

Introduction to Statistics: Political Science (Class 3). Calculating R-Squared, Dichotomous and Nominal Variables, F-tests. R-Squared. Coef. St.Err T P Bush FT -.090 .489 -0.18 0.860 Party Identification 12.31 7.47 1.65 0.143

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Multiple Regression Analysis

Multiple Regression Analysis. y = b 0 + b 1 x 1 + b 2 x 2 + . . . b k x k + u 6. Heteroskedasticity. What is Heteroskedasticity. Recall the assumption of homoskedasticity implied that conditional on the explanatory variables, the variance of the unobserved error, u , was constant

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Multiple Regression Applications

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Probabilistic Privacy Analysis of Published Views

Probabilistic Privacy Analysis of Published Views. Hui (Wendy) Wang Laks V.S. Lakshmanan University of British Columbia Vancouver, Canada. Motivation. Publishing relational data containing personal information Sensitive information: private associations E.g., Bill gets AIDS

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Charles Z. Liu, University of Pittsburgh Chris F. Kemerer, University of Pittsburgh

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Hasse Diagrams for Linear Models

Hasse Diagrams for Linear Models. 2006 Professional Bowlers Association Qualifying Scores. Description. 2006-7 Pro Bowlers Association Tournaments Bowlers: 37 Bowlers Competing in all Tournaments Oil Patterns: 5 Patterns Used (Chameleon, Cheetah, Scorpion, Shark, Viper)

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Introduction to Econometrics

Introduction to Econometrics. Lecture 6 Testing restrictions. Lecture plan. Testing restrictions about individual parameters groups of parameters. t-tests for individual parameters zero value under H 0 Some other value under H 0. F-tests for groups of parameters

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V17 (Money as a means of Exchange)

V17 (Money as a means of Exchange). Money Exchange vs. Culture. TJ Salunga Professor Dr. White Antrho 174W. Hypothesis & independent/dependent variables.

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Data

Unrestricted Model. Data. Theory. t-statistics. Restricted Model (excludes independent variables with low t-stats). F-statistic. Unrestricted Model. Data. Theory. Examine t-statistics. Restricted Model (excludes independent variables with t-stats below critical-t).

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