We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byAbigail Lopez
Modified over 3 years ago
Page 1© Crown copyright 2004 Skill scores for GEMS-aerosol Olivier Boucher GEMS - Kick-off meeting July 2005
Page 2© Crown copyright 2004 Skill scores - Correlation coefficients (observed vs simulated aerosol properties) - current models perform well on monthly means - challenge will be to get good correlation on daily means - Linear fits: slope, offset - Root-mean square errors - largely used in RAQ - Taylor diagrams - summarizes model performance in terms of correlation coefficient, standard deviation, and RMS. - Figures of merit - useful to test the transport for particular events - has been used for ETEX
Page 3© Crown copyright 2004 Skill scores - Figures of merit - useful to test the transport for particular events - has been used for ETEX Time Concentration AOD Obs Model Merit=blue area/green area
Page 1© Crown copyright 2004 AER sub-project: report to GEMS plenary Olivier Boucher GEMS - Kick-off meeting July 2005.
Linear Prediction Correlation can be used to make predictions – Values on X can be used to predict values on Y – Stronger relationships between X and Y.
Copyright © 2008 Pearson Education, Inc. Chapter 1 Linear Functions Copyright © 2008 Pearson Education, Inc.
LINEAR REGRESSION: Evaluating Regression Models. Overview Standard Error of the Estimate Goodness of Fit Coefficient of Determination Regression Coefficients.
GEMS-Aerosol WP_AER_4: Evaluation of the model and analysis Lead Partners: NUIG & CNRS-LOA Partners: DWD, RMIB, MPI-M, CEA- IPSL-LSCE,ECMWF, DLR (at no.
Managerial Economics Demand Estimation. Scatter Diagram Regression Analysis.
Aim: Review for Exam Tomorrow. Independent VS. Dependent Variable Response Variables (DV) measures an outcome of a study Explanatory Variables (IV) explains.
Correlation. Correlation is a measure of the strength of the relation between two or more variables. Any correlation coefficient has two parts – Valence:
Regression and Correlation of Data Correlation: Correlation is a measure of the association between random variables, say X and Y. No assumption that one.
Measures of dispersion Standard deviation (from the mean) ready.
6-1 Introduction To Empirical Models Based on the scatter diagram, it is probably reasonable to assume that the mean of the random variable Y is.
Regression Analysis Deterministic model No chance of an error in calculating y for a given x Probabilistic model chance of an error First order linear.
1 Review of Correlation A correlation coefficient measures the strength of a linear relation between two measurement variables. The measure is based on.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 12 Analyzing the Association Between Quantitative Variables: Regression Analysis Section.
Date of download: 6/22/2016 Copyright © 2016 American Medical Association. All rights reserved. From: Effects of Graft Thickness and Asymmetry on Visual.
5.4 Line of Best Fit Given the following scatter plots, draw in your line of best fit and classify the type of relationship: Strong Positive Linear Strong.
AP STATISTICS LESSON 3 – 3 (DAY 2) The role of r 2 in regression.
LINEAR REGRESSION: Evaluating Regression Models. Overview Assumptions for Linear Regression Evaluating a Regression Model.
LINEAR REGRESSION: Evaluating Regression Models Overview Assumptions for Linear Regression Evaluating a Regression Model.
Operational verification system Rodica Dumitrache National Metorogical Administration ROMANIA.
A medical researcher wishes to determine how the dosage (in mg) of a drug affects the heart rate of the patient. DosageHeart rate
6-1 Introduction To Empirical Models Based on the scatter diagram, it is probably reasonable to assume that the mean of the random variable Y.
L Berkley Davis Copyright 2009 MER301: Engineering Reliability Lecture 12 1 MER301: Engineering Reliability LECTURE 12: Chapter 6: Linear Regression Analysis.
LECTURE 9 Tuesday, 24 FEBRUARY STA291 Fall Administrative 4.2 Measures of Variation (Empirical Rule) 4.4 Measures of Linear Relationship Suggested.
Chapter 13. Understand and interpret the terms dependent and independent variable. Calculate and interpret the coefficient of correlation, the coefficient.
Prepared by Robert F. Brooker, Ph.D. Copyright ©2004 by South-Western, a division of Thomson Learning. All rights reserved.Slide 1 Managerial Economics.
Chapter 6 (cont.) Difference Estimation. Recall the Regression Estimation Procedure 2.
McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 13 Linear Regression and Correlation.
Correlation and Linear Regression Chapter 13 McGraw-Hill/Irwin Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved.
Method 3: Least squares regression. Another method for finding the equation of a straight line which is fitted to data is known as the method of least-squares.
Time Series 2 Time Series 1 R 2 = 1 Perfectly correlated TS2=5*cos(2*t) TS1=cos(2*t)
Variance Stabilizing Transformations. Variance is Related to Mean Usual Assumption in ANOVA and Regression is that the variance of each observation is.
Kin 304 Regression Linear Regression Least Sum of Squares Assumptions about the relationship between Y and X Standard Error of Estimate Multiple Regression.
Regression, Correlation. Research Theoretical empirical Usually combination of the two.
REGRESSION Predict future scores on Y based on measured scores on X Predictions are based on a correlation from a sample where both X and Y were measured.
Section 5.2: Linear Regression: Fitting a Line to Bivariate Data.
Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 1 ~ Curve Fitting ~ Least Squares Regression Chapter.
ECON 338/ENVR 305 CLICKER QUESTIONS Statistics – Question Set #8 (from Chapter 10)
Date of download: 6/17/2016 Copyright © 2016 SPIE. All rights reserved. Location of the study area within the Bay of Biscay and oceanographic sampling.
Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 171 CURVE.
Chapter 3 Correlation. Association between scores on two variables –e.g., age and coordination skills in children, price and quality.
Correlation and Prediction Error The amount of prediction error is associated with the strength of the correlation between X and Y.
American Seas NCOM Assessments and Graphics for JUNE 2010 Frank Bub – NAVOCEANO (16 FEB 11) File: AMSEAS_GOM_NCOM_Evals_all_16FEB11.ppt June coverage –
Learning Objectives Copyright © 2004 John Wiley & Sons, Inc. Bivariate Correlation and Regression CHAPTER Thirteen.
Copyright 2002 David M. Hassenzahl Using r and 2 Statistics for Risk Analysis.
Chimiometrie 2009 Proposed model for Challenge2009 Patrícia Valderrama
Effects Of Different Model Lower Boundary Conditions In The Simulation Of An Orographic Precipitation Extreme Event J. Teixeira, A. C. Carvalho, T. Luna.
Correlation and Regression Basic Concepts. An Example We can hypothesize that the value of a house increases as its size increases. Said differently,
Past and Projected Changes in Continental-Scale Agro-Climate Indices Adam Terando NC Cooperative Research Unit North Carolina State University 2009 NPN.
© 2017 SlidePlayer.com Inc. All rights reserved.