'Linear correlation' diaporamas de présentation

Speech: Fundamentals CS 3710 / ISSP 3565

Speech: Fundamentals CS 3710 / ISSP 3565. (Slides modified from D. Jurafsky ). Outline. Acoustic Phonetics and Signals Prosodic Analysis. The Big Picture. Chapter 7: The idea that the spoken word is composed of smaller units of speech is implicit in sound-based writing systems

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gapminder

Discovering patterns in data: correlation and visualization. www.gapminder.org. Will Hamilton April 2017. Contents. PART 2: Data visualisation Rules for good graphing Bad graphs. PART 1: Correlation What is correlation? Types of correlation Linear regression Multiple linear regression

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Mutidimensional Data Analysis

Mutidimensional Data Analysis. Growth of big databases requires important data processing. ? Need for having methods allowing to extract this information from large data tables. Tree categories of Data Analysis methods : Description : to describe a phenomenon without prejudice

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Correlation and Regression

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Chapter 4 Describing the Relation Between Two Variables

Chapter 4 Describing the Relation Between Two Variables. 4.1 Scatter Diagrams; Correlation. Bivariate data is data in which two variables are measured on an individual.

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Lecture Slides

Lecture Slides. Elementary Statistics Twelfth Edition and the Triola Statistics Series by Mario F. Triola. Chapter 10 Correlation and Regression. 10-1 Review and Preview 10-2 Correlation 10-3 Regression 10-4 Prediction Intervals and Variation 10-5 Multiple Regression

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Graphs

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Effects of Fall Fertilization, Taxonomic Differences and Light Intensity on Freeze Resistance of Azaleas

Effects of Fall Fertilization, Taxonomic Differences and Light Intensity on Freeze Resistance of Azaleas. Frank Henning R4 EPA-LGU Liaison fhenning@uga.edu. Rhododendron economically important Varieties with desired horticultural traits susceptible to freeze damage. Leaf Retention.

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Velocity bunching from S-band photoinjectors

Velocity bunching from S-band photoinjectors. Julian McKenzie 1 st July 2011 Ultra Bright Electron Sources Workshop Cockcroft Institute STFC Daresbury Laboratory, UK. Introduction. Normal conducting S-band RF guns are often the gun of choice for modern FELs

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Statistics Bivariate Analysis

Minutes Exercised Per Day vs. Weighted GPA. Statistics Bivariate Analysis. By: Student 1, 2, 3. Why did we choose this study?. Exercise is a vital part of staying healthy and living an active and accomplished lifestyle.

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WSR-88D Signatures Associated with One Inch Hail in the Southern Plains

WSR-88D Signatures Associated with One Inch Hail in the Southern Plains. Dennis E. Cavanaugh Jessica A. Schultz National Weather Service Weather Forecast Office Fort Worth, TX. Motivation. January 2010: NWS changed Severe Thunderstorm Warning

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Overview Chapter 9

Overview Chapter 9.

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Upper GI Bleed

Upper GI Bleed. Leigh Vaughan, MD April 30, 2013 Division of Hospital Medicine General Internal Medicine and Geriatrics, MUSC. Objectives . Identify common causes for acute gastrointestinal bleeding in the hospitalized patient

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Analyze the following graph!

Analyze the following graph!. Chapter 1 & 3 The Role of Statistics & Graphical Methods for Describing Data. Descriptive statistics. the methods of organizing & summarizing data. If the sample of high school GPAs contained 10,000 numbers, how could the data be described or summarized?.

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Line of Best Fit

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Estimating Surface PM 2.5 Concentrations using Satellite AOD

Estimating Surface PM 2.5 Concentrations using Satellite AOD. Sundar A. Christopher The University of Alabama in Huntsville sundar@nsstc.uah.edu VIIRS Aerosol Science and Operational Users Workshop November 21-22, 2013.

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Causality and confounding variables

Causality and confounding variables. Scientists aspire to measure cause and effect Correlation does not imply causality. Hume: contiguity + order (cause then effect) + effect only when cause present

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Ik Hee Ryu , Hun Yang, David S. Kang, Jin Kuk Kim BS Clean Vision Eye center

Comparison of the Topographic Optical Zone After LASIK for Myopic Astigmatism With 2 Excimer Laser Platforms. Ik Hee Ryu , Hun Yang, David S. Kang, Jin Kuk Kim BS Clean Vision Eye center The authors have no financial interest in the subject matter of this e-poster.

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15.5 Linear Correlation Objectives:

15.5 Linear Correlation Objectives:. Be able to construct a scatterplot to show the relationship between two variables. Understand the properties of the linear correlation coefficient. Be able to use your calculator to compute the linear correlation coefficient . Scatterplots.

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Time Series 2 Time Series 1

Time Series 2 Time Series 1. TS2=5*cos(2*t) TS1=cos(2*t). R 2 = 1 Perfectly correlated. Time Series 2 Time Series 1. *. R 2 = 0 No LINEAR correlation. TS2=5*cos(2*t) TS1=cos(t). Time Series 1 Time Series 2. TS1=sin(t) TS2=cos(t). R 2 = 0 No correlation. Time Series 2

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