'Overall mean' presentation slideshows

3F4 Line Coding

3F4 Line Coding. Dr. I. J. Wassell. Introduction. Line coding is the procedure used to convert an incoming bit stream, b k to symbols a k which are then sent as pulses a k h T (t-kT) on to the channel The line coding technique affect the properties of the transmitted signal

856 views • 53 slides

Central Tendency

Central Tendency. Introduction to Statistics Chapter 3 Jan 26, 2010 Class #3. Central Tendency. A statistical measure to determine a single score that defines the center of the distribution There are many measures of central tendency. The most common are the mean, median, and mode .

780 views • 44 slides

Chapter 12

Chapter 12. Analysis of Variance. Goals. List the characteristics of the F distribution Conduct a test of hypothesis to determine whether the variances of two populations are equal Discuss the general idea of analysis of variance Organize data into a ANOVA table

523 views • 36 slides

Linear Modelling II

Linear Modelling II. Richard Mott Wellcome Trust Centre for Human Genetics. Recap. So far, we have learnt about Correlation Linear Regression One-Way Analysis of Variance Non-parametric alternatives In this lecture we will cover Relationship between Least Squares and Max Likelihood

437 views • 34 slides

Chapter 9: Interpretative aspects of correlation and regression

Chapter 9: Interpretative aspects of correlation and regression. r=-0.83, Regression line: Y'=-0.83X+0.00. r=-0.83, Regression line: Y'=-0.5X+41.5. 2. 40. 1. zy. y. 30. 0. 20. -1. 10. 20. 30. 40. -3. -2. -1. 0. 1. x. zx. Fun facts about the regression line.

365 views • 29 slides

Introduction

Part III The General Linear Model. Multiple Explanatory Variables Chapter 12 Multiple Regression. Introduction. GLM, one explanatory: Regression: t-test/ANOVA: GLM, multiple explanatory: Multiple Regression Multi-way ANOVA ANCOVA .

343 views • 20 slides

Analysis of Variance (ANOVA)

Analysis of Variance (ANOVA). When ANOVA is used. All the explanatory variables are categorical (factors) Each factor has two or more levels

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Purpose

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