'New variables' diaporamas de présentation

Ensemble Forecasting

Ensemble Forecasting. Yuejian Zhu Ensemble & Probabilistic Guidance Team Environmental Modeling Center December 7 th 2010 Acknowledgment for: Jun Du, Dingchen Hou, Geoff DiMego, John Ward, Hendrik Tolman Bill Lapenta and Steve Lord. Outline. Service for users

1.83k views • 75 slides

Overview of the National Health Care Survey

Overview of the National Health Care Survey. Linda K. Demlo, Ph.D. Amy Bernstein, Sc.D. Division of Health Care Statistics National Center for Health Statistics July 16, 2002 2002 NCHS Data Users Conference. National Center for Health Statistics. Session Objectives.

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Data analysis: cross-tabulation

GAP Toolkit 5 Training in basic drug abuse data management and analysis. Data analysis: cross-tabulation. Training session 11. Objectives. To introduce cross-tabulation as a method of investigating the relationship between two categorical variables

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RE-SEED Training Inquiry Based Learning Workshop

RE-SEED Training Inquiry Based Learning Workshop. About the Program. Christos Zahopoulos , Executive Director Claire Duggan, Director of Programs Daniel Sullivan, Program Coordinator. About the Program. Mary Howley , Administrative Officer Feby Kiragu , Administrative Officer.

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SPSS Tutorial

SPSS Tutorial. AEB 37 / AE 802 Marketing Research Methods Week 5. SPSS. You can open an excel file directly from SPSS SPSS files contain additional information on the variables Download the following file on your network drive: www.rdg.ac.uk/~aes02mm/supermarkets.sav Start SPSS

3.68k views • 25 slides

Kernelization

Mashrur Alam Khan School of Computer Science University of Waterloo Canada. Kernelization. Outline. Background Materials A Closer Look at Some Parameterized Problems p -MAX-3-SAT p -FAST p -d-Hitting Set p -Dominating Set on Planar Graph p -Max Leaf Tree Conclusions and Future Work.

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Incorporating Nonmetric Data with Dummy Variables

Incorporating Nonmetric Data with Dummy Variables. The logic of dummy-coding Dummy-coding in SPSS. Dummy-coding variables.

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Stata and logit recap

Stata and logit recap. Topics. Introduction to Stata Files / directories Stata syntax Useful commands / functions Logistic regression analysis with Stata Estimation Goodness Of Fit Coefficients Checking assumptions. Overview of Stata commands.

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Adding Value to Travel Behavior Surveys:

Adding Value to Travel Behavior Surveys:. The Network Analyst Approach. Presentation by: Kearey L. Smith Stella Wotherspoon Metropolitan Transportation Commission San Francisco Bay Area, CA. August 10, 2006. ESRI User Conference 2006 San Diego, CA. Bay Area Travel Survey 2000.

485 views • 18 slides

Basic Data Analysis

Basic Data Analysis . Tabulation. Frequency table Percentages. A Typical Table. Type of Measurement. Type of descriptive analysis. Nominal. Cross Tabs Mode. Type of Measurement. Type of descriptive analysis. Ordinal. Rank order Median. Type of Measurement. Type of

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ABINIT INPUT MAKER

ABINIT INPUT MAKER. By Simon Pesant and BenjaminTardif. 29/01/2007. Summary. A brief presentation of the program and his advantage The implementation of Abinit Input Maker The XML file format The validation of the values Addition of another section in Abinit Input Maker Conclusion.

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General issues using MATLAB

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Canonical correlations

Canonical correlations. Purpose Calculation of canonical correlations Relevance to prediction Relevance to correspondence analysis R commands. Purpose.

456 views • 11 slides

General good advice on data handling

General good advice on data handling. Peter Shaw. Introduction. We have spent the last 11 weeks engaged in picking up some technical details about various aspects of data handling and analysis.

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The Combined Gas Law

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6-6 Placing Figures in the Coordinate Plane

6-6 Placing Figures in the Coordinate Plane. L.E.Q. How do you use properties of special figures to name missing coordinates?. Example 1: Naming Coordinates. In the diagram, rectangle KLMN is centered at the origin with sides parallel to the axes. Find the missing coordinates of K, M, and N.

705 views • 6 slides

SIRS Model

SIRS Model. Richard George. SIRS Model. Susceptible Infected Removed Disease Clustering. Math Describing the Model. Code. New variables taken into consideration Histogram showing distribution of surrounding Infected/removed neighbors. Results. (Display code running SIR and SIRS with

332 views • 5 slides