Analysis of Variance (ANOVA) Indian Institute of Public Health Delhi MSc CR 2013-15 Outline of the session • Need for Analysis of Variance • Concept behind one way ANOVA • Example • Non-parametric alternative When dependent variable is continuous Type of Dependent variable Type of Independent variable Number of Groups Continuous Categorical More than two Non-parametric (Wilcoxon sign rank) Paired t – test Not normal Non-parametric (Wilcoxon sign
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Variance (ANOVA) Dr. H. Johnson ANOVA • Analysis of variance (ANOVA) is a powerful hypothesis testing procedure that extends the capability of t-tests beyond just two samples. • Many types of ANOVAs‚ today we will learn about a oneway independent-measures ANOVA • Later we’ll learn one-way repeated-measures ANOVA . • We’ll also learn two-factor ANOVA after that. • These ANOVAs are by no means all of them! There are a LOT more types! One-Way ANOVA • The independent measures ANOVA is used
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Chapter 15: Introduction to the Design of Experimental and Observational Studies The Models in Analysis of Variance(ANOVA) and in Regression are different. In regression model‚ all the response and predictors are continuous (quantitative) variables. However‚ in ANOVA model‚ the response is continuous but the predictors are categorical (qualitative) variables. There are some concepts here. 1. Factor and factor level. A factor is a predictor (explanatory or independent) variable. A factor level is
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ANOVA Hypothesis Testing Paper RES/342 July 5‚ 2011 University of Phoenix ANOVA Hypothesis Testing Paper According to Payscale.com an individual with a high school education entering the work force will earn less than an individual with the same level of education who has worked longer in that particular field (Harrison‚ 2010). Team A has selected data from the Wages and Wage Earners data set and will be using the analysis of variance‚ also known as ANOVA‚ to compare the mean of age
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variances (ANOVA) One way ANOVA: A One-Way Analysis of Variance is a way to test the equality of three or more means at one time by using variances. Two way ANOVA: A Two-Way ANOVA is useful when we desire to compare the effect of multiple levels of two factors and we have multiple observations at each level. Grand Mean The grand mean of a set of samples is the total of all the data values divided by the sample size. It turns out that all that is necessary to find perform a one-way analysis
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Iqra University‚ Main Campus Course: Statistical Inferences Faculty: Iftikhar Mubbashir Date: December 5‚ 2013 Fall 2013 Statistics-Walpole Chapter-12 One way Classification • • • • • • Random samples of size n are selected from each of k populations. The k populations are independent and normally distributed with means µ 1 ‚ µ 2 ‚K ‚ µ k and common variance σ 2 . We wish to derive appropriate methods for testing the hypothesis:
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Submit your answers to the following questions using the ANOVA source table below. The table depicts a two-way ANOVA in which gender has two groups (male and female)‚ marital status has three groups (married‚ single never married‚ divorced)‚ and the means refer to happiness scores (n = 100): What is/are the independent variable(s)? What is/are the dependent variable(s)? What would be an appropriate null hypothesis? Alternate hypothesis? What are the degrees of freedom for 1) gender‚ 2) marital
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THE LOGIC OF ANOVA ANalysis Of VAriance (commonly abbreviated as ANOVA)‚ more specifically‚ we will take up an application known as one-way ANOVA. Many statisticians think of ANOVA as an extension of the difference of means test because it’s based‚ in part‚ on a comparison of sample means. At the same time‚ however‚ the procedure involves a comparison of different estimates of population variance—hence the name analysis of variance. Because ANOVA is appropriate for research involving three or
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Applying ANOVA and Non Parametric Tests a. What are three lessons you learned relative ANOVA and Nonparametric tests? While doing the simulation; the three lessons learned are as follows: Monitor – the situation Measure – provide measurements‚ accumulate data Improve – provide solutions for improvement. b. As a result of using this simulation‚ what concepts and analytic tools will you be able to use in your workplace (i.e.‚ how do you expect to apply what you learned)? As a result of using
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to: Recognize situations in which to use analysis of variance Understand different analysis of variance designs Perform a single-factor hypothesis test and interpret results Conduct and interpret post-analysis of variance pairwise comparisons procedures Set up and perform randomized blocks analysis Analyze two-factor analysis of variance test with replications results Business Statistics: A Decision-Making Approach‚ 6e © 2005 Prentice-Hall‚ Inc. Business Statistics: A Decision-Making Approach
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