Analysis of Variance Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.

Slides:



Advertisements
Similar presentations
Copyright (c) 2004 Brooks/Cole, a division of Thomson Learning, Inc. Chapter 10 The Analysis of Variance.
Advertisements

Randomized Complete Block and Repeated Measures (Each Subject Receives Each Treatment) Designs KNNL – Chapters 21,
Chapter 11 Analysis of Variance
Design of Experiments and Analysis of Variance
N-way ANOVA. Two-factor ANOVA with equal replications Experimental design: 2  2 (or 2 2 ) factorial with n = 5 replicate Total number of observations:
Probability & Statistical Inference Lecture 8 MSc in Computing (Data Analytics)
The Two Factor ANOVA © 2010 Pearson Prentice Hall. All rights reserved.
© 2010 Pearson Prentice Hall. All rights reserved Single Factor ANOVA.
1 1 Slide © 2009, Econ-2030 Applied Statistics-Dr Tadesse Chapter 10: Comparisons Involving Means n Introduction to Analysis of Variance n Analysis of.
Correlation and Simple Regression Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.
Independent Sample T-test Formula
Inference Procedures for Two Populations Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.
Estimation and Testing for Population Proportions Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.
Multiple Linear Regression Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.
Lesson #23 Analysis of Variance. In Analysis of Variance (ANOVA), we have: H 0 :  1 =  2 =  3 = … =  k H 1 : at least one  i does not equal the others.
Chapter 3 Analysis of Variance
Chapter 14 Conducting & Reading Research Baumgartner et al Chapter 14 Inferential Data Analysis.
1 Pertemuan 13 Analisis Ragam (Varians) - 2 Matakuliah: I0272 – Statistik Probabilitas Tahun: 2005 Versi: Revisi.
1 Pertemuan 10 Analisis Ragam (Varians) - 1 Matakuliah: I0262 – Statistik Probabilitas Tahun: 2007 Versi: Revisi.
Chi-Square and F Distributions Chapter 11 Understandable Statistics Ninth Edition By Brase and Brase Prepared by Yixun Shi Bloomsburg University of Pennsylvania.
Chapter 12: Analysis of Variance
1 1 Slide © 2006 Thomson/South-Western Slides Prepared by JOHN S. LOUCKS St. Edward’s University Slides Prepared by JOHN S. LOUCKS St. Edward’s University.
1 1 Slide © 2005 Thomson/South-Western Chapter 13, Part A Analysis of Variance and Experimental Design n Introduction to Analysis of Variance n Analysis.
1 1 Slide © 2008 Thomson South-Western. All Rights Reserved Chapter 13 Experimental Design and Analysis of Variance nIntroduction to Experimental Design.
Copyright © 2013, 2010 and 2007 Pearson Education, Inc. Chapter Comparing Three or More Means 13.
ANOVA One Way Analysis of Variance. ANOVA Purpose: To assess whether there are differences between means of multiple groups. ANOVA provides evidence.
One-Factor Analysis of Variance A method to compare two or more (normal) population means.
Chapter 10 Analysis of Variance.
Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap th Lesson Analysis of Variance.
©2003 Thomson/South-Western 1 Chapter 11 – Analysis of Variance Slides prepared by Jeff Heyl, Lincoln University ©2003 South-Western/Thomson Learning™
Copyright © 2004 Pearson Education, Inc.
Comparing Three or More Means ANOVA (One-Way Analysis of Variance)
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
Lecture 9-1 Analysis of Variance
Module 18: One Way ANOVA Reviewed 11 May 05 /MODULE 18 This module begins the process of using variances to address questions about means. Strategies.
Chapter 12: Analysis of Variance. Chapter Goals Test a hypothesis about several means. Consider the analysis of variance technique (ANOVA). Restrict the.
Previous Lecture: Phylogenetics. Analysis of Variance This Lecture Judy Zhong Ph.D.
Chapter 10: Analysis of Variance: Comparing More Than Two Means.
Chapter 8 1-Way Analysis of Variance - Completely Randomized Design.
Copyright © Cengage Learning. All rights reserved. 12 Analysis of Variance.
Comparison of groups The purpose of analysis is to compare two or more population means by analyzing sample means and variances. One-way analysis is used.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
Econ 3790: Business and Economic Statistics Instructor: Yogesh Uppal
Econ 3790: Business and Economic Statistics Instructor: Yogesh Uppal
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved Lecture Slides Elementary Statistics Eleventh Edition and the Triola.
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Overview and One-Way ANOVA.
1/54 Statistics Analysis of Variance. 2/54 Statistics in practice Introduction to Analysis of Variance Analysis of Variance: Testing for the Equality.
ENGR 610 Applied Statistics Fall Week 8 Marshall University CITE Jack Smith.
Aron, Aron, & Coups, Statistics for the Behavioral and Social Sciences: A Brief Course (3e), © 2005 Prentice Hall Chapter 10 Introduction to the Analysis.
Chapter 8 Analysis of METOC Variability. Contents 8.1. One-factor Analysis of Variance (ANOVA) 8.2. Partitioning of METOC Variability 8.3. Mathematical.
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Lecture Slides Elementary Statistics Tenth Edition and the.
Copyright © 2008 by Hawkes Learning Systems/Quant Systems, Inc.
SEMINAR ON ONE WAY ANOVA
Factorial Experiments
An Introduction to Two-Way ANOVA
i) Two way ANOVA without replication
Chapter 10: Analysis of Variance: Comparing More Than Two Means
Categorical Variables
Chapter 11 – Analysis of Variance
Categorical Variables
Chapter 11: The ANalysis Of Variance (ANOVA)
MOHAMMAD NAZMUL HUQ, Assistant Professor, Department of Business Administration. Chapter-16: Analysis of Variance and Covariance Relationship among techniques.
Lecture Slides Elementary Statistics Eleventh Edition
One way ANALYSIS OF VARIANCE (ANOVA)
Chapter 10 Introduction to the Analysis of Variance
Chapter 15 Analysis of Variance
Statistical Inference for the Mean: t-test
ANalysis Of VAriance Lecture 1 Sections: 12.1 – 12.2
STATISTICS INFORMED DECISIONS USING DATA
Presentation transcript:

Analysis of Variance Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Assumptions The replicates are obtained independently and randomly from each of the populations. The replicates from each population follow a (approximate) normal distribution. The normal populations all have a common variance. Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Measuring Variation SS(factor) measures between-sample variation [SS(between)] SS(error) measures within-sample variation [SS(within)] SS(total) measures the total variation in the sample [SS(factor)] [SS(error)] Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Determining Sum of Squares Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Anova Table Source df SS MS F Factor k - 1SS(factor)MS(factor)MS(factor) Error n - 2SS(error)MS(error)MS(error) Total n - 1SS(total) MS(factor)  SS(factor) k  1 MS(factor) MS(error)  SS(error) n  k F = Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Test for Equal Variances H o :  1 2 =  2 2 = …. =  k 2 H a : At least 2 variances are unequal Reject H O if H > H Table A.14 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Confidence Intervals in One Factor ANOVA Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Multiple Comparisons Procedure Find Q , k,  using Table A.16 Determine Place the sample means in order, from smallest to largest. If two means differ by more than D, the conclusion is that the corresponding population means are unequal. Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

One-Factor ANOVA Procedure Requirements The replicates are obtained independently and randomly from each of the populations. The observations from each population follow (approximately) a normal distribution. The populations all have a common variance. Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

H o  1 =  2 = … =  k H a not all  ’s are equal Source df SS MS F Factor k - 1SS(factor)MS(factor)MS(factor) Error n - 2SS(error)MS(error)MS(error) Total n - 1SS(total) Reject H o if F * > F , k-1,n-1 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Randomized Block Design Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing The samples are not independent, the data are grouped (blocked) by another variable. The difference between the randomized block design and the completely randomized design is that here we use a blocking strategy rather than independent samples to obtain a more precise test for examining differences in the factor level means.

Randomized Block Design k = number of factor levels in the design b = number of blocks in the design n = number of observations = bk Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Factor Hypothesis Test H o  1 =  2 = … =  k H a not all  ’s are equal Reject H o if F * > F , k-1, (k-1)(b-1) Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Block Hypothesis Test H o  1 =  2 = … =  b H a not all  ’s are equal Reject H O if F * > F , b-1, (k-1)(b-1) Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Confidence Interval Difference Between Two Means Randomized Block (1-  ) 100% Confidence Interval Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Multiple Comparisons Procedure: Randomized Block Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing | X i  X j | > D

Two-Way Factorial Design Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Hypothesis Test Factor A H o Factor A is not significant H a Factor A is significant Reject H o,A if F 1 > F ,  1,  2 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Hypothesis Test Factor B H o Factor B is not significant H a Factor B is significant Reject H o,B if F 2 > F ,  1,  2 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Hypothesis Test Interaction H o Interaction is not significant H a Interaction is significant Reject H o,AB if F 2 > F ,  1,  2 Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing

Multiple Comparisons Procedure: Two-Way Factorial Design Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing