'Statistical software packages' diaporamas de présentation

Analysis of Variance

Analysis of Variance. Review and Preview One-Way ANOVA Two-Way ANOVA. Overview and One-Way ANOVA. Key Concept. This section introduces the method of one-way analysis of variance , which is used for tests of hypotheses that three or more population means are all equal. Overview.

955 views • 63 slides

Multiple Linear Regression and Correlation Analysis

Multiple Linear Regression and Correlation Analysis. Chapter 14. GOALS. Describe the relationship between several independent variables and a dependent variable using multiple regression analysis .

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Chapter 12 Significance Tests in Practice

Chapter 12 Significance Tests in Practice. AP Statistics Hamilton/Mann. Introduction. In Chapter 11, we made the unrealistic claim that we knew the population standard deviation ?. In this chapter, we will stop making this assumption.

672 views • 53 slides

Comparison of 2 Population Means

Comparison of 2 Population Means. Goal: To compare 2 populations/treatments wrt a numeric outcome Sampling Design: Independent Samples (Parallel Groups) vs Paired Samples (Crossover Design) Data Structure: Normal vs Non-normal Sample Sizes: Large ( n 1 , n 2 >20) vs Small. Independent Samples.

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1-Way Analysis of Variance

1-Way Analysis of Variance. Setting: Comparing g > 2 groups Numeric (quantitative) response Independent samples Notation (computed for each group): Sample sizes: n 1 ,..., n g ( N=n 1 +...+ n g ) Sample means: Sample standard deviations: s 1 ,..., s g. 1-Way Analysis of Variance.

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Comparison of 2 Population Means

Comparison of 2 Population Means. Goal: To compare 2 populations/treatments wrt a numeric outcome Sampling Design: Independent Samples (Parallel Groups) vs Paired Samples (Crossover Design) Data Structure: Normal vs Non-normal Sample Sizes: Large ( n 1 , n 2 >20) vs Small. Independent Samples.

490 views • 29 slides

Introduction to Survey Data Analysis

Introduction to Survey Data Analysis. Linda K. Owens, PhD Assistant Director for Sampling & Analysis Survey Research Laboratory University of Illinois at Chicago. Focus of the seminar. Data cleaning/missing data Sampling bias reduction. When analyzing survey data.

619 views • 29 slides

Statistics Canada Research Data Centre Program*

470 views • 29 slides

Comparison of 2 Population Means

Comparison of 2 Population Means. Goal: To compare 2 populations/treatments wrt a numeric outcome Sampling Design: Independent Samples (Parallel Groups) vs Paired Samples (Crossover Design) Data Structure: Normal vs Non-normal Sample Sizes: Large ( n 1 , n 2 >20) vs Small. Independent Samples.

423 views • 29 slides

Reliability

Reliability. Consistency in testing. Types of variance. Meaningful variance Variance between test takers which reflects differences in the ability or skill being measured Error variance

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Bivariate Statistics

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Model Driven DSS

Model Driven DSS. Chapter 9. What is a Model?. A mathematical representation that relates variables For solving a decision problem Convert the decision problem into a model There can be multiple solutions to a model Use math techniques solve the model. Environmental factors.

946 views • 19 slides

MIDDLE-EASTERN COUNTRIES

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Mark D. Skowronski Computational Neuro-Engineering Lab Electrical and Computer Engineering

Statistical automatic identification of microchiroptera from echolocation calls Lessons learned from human automatic speech recognition. Mark D. Skowronski Computational Neuro-Engineering Lab Electrical and Computer Engineering University of Florida Gainesville, FL, USA December 1, 2004.

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Correlation

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Regression Approach To ANOVA

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Multimedia Data Mining

Multimedia Data Mining. Arvind Balasubramanian arvind@utdallas.edu Multimedia Lab The University of Texas at Dallas. Me and My Research. Research Interests: Machine Learning Data Mining Statistical Analysis Applications of the above in Multimedia I am currently working on

638 views • 15 slides

Generalized Linear Models

Generalized Linear Models. Generalized Linear Models (GLM). General class of linear models that are made up of 3 components: Random, Systematic, and Link Function Random component: Identifies dependent variable ( Y ) and its probability distribution

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Warm- up

Warm- up. Use the weight lifter warmup - Printed. Computer Regression. Section 3.3D. Computer Software. There are two statistical software packages that are often used Minitab JMP Once you understand the statistical ideas, you can read and work with almost any software output.

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GAISE: Use Technology For Developing Concepts & Analyzing Data

Workshop on Teaching Introductory Statistics Sessions 6 & 7: Using Technology in the Classroom, Parts I & II. Roger Woodard, North Carolina State University Ginger Holmes Rowell, Middle Tennessee State University Medical College of Wisconsin in Milwaukee July 10-13, 2006.

196 views • 10 slides