PPT-Factorial ANOVA Chapter 14

People can be divided into two classes Those who go ahead and do something and those who sit still and inquire Why wasnt it done the other way Oliver Wendell Holmes American Physician Writer . within block Must do some sort of incomplete block analysis If you do not certain eects confounded Confounding two eects are indistinguishable May sacrice certain eects thought to be small design makes setup simple 241 Confounding in with only 2 blo NR 245. Austin Troy. Based primarily on material accessed from Garson, G. David 2010. . Univariate GLM, ANOVA, and ANCOVA. . Statnotes. : Topics in Multivariate Analysis.. http://faculty.chass.ncsu.edu/garson/PA765/statnote.htm. Analysis of Variation. Math 243 Lecture. R. Pruim. The basic ANOVA situation. Two variables: 1 Categorical, 1 Quantitative. Main Question: Do the (means of) the quantitative variables depend on which group (given by categorical variable) the individual is in?. Cal State Northridge. . 320. Andrew Ainsworth PhD. Topics in Factorial Designs. What is Factorial?. Assumptions. Analysis. Multiple Comparisons. Main Effects. Simple Effects. Simple Comparisons. Effect Size estimates. Chapter 8. Experimental Design II: Factorial Designs. Chapter Objectives. Describe factorial designs using a standardized notation system (2x2, 3x5, etc.) and place data accurately into a factorial matrix to calculate row and column means. (a.k.a. Analysis of Variance). 1. Outline:. Testing for a difference. in means. Notation. Sums of squares. Mean. squares. The. F distribution. The. ANOVA table. Part II: multiple. comparisons. Worked example. Analysis of Variance. Let’s say we conduct this experiment: effects of alcohol on memory. Basic Design. Grouping variable . (IV, manipulation) with . 2 or more levels. Continuous dependent/criterion variable. Research Methods in Physical Activity. Research Methods in Physical Activity. Purpose and Protocol of the Statistical Test. The purpose of the statistical test is to evaluate the null hypothesis at a specific level of probability (e.g., p < .05). In other words, do the two levels of treatment differ significantly (p < .05) so that these differences are not attributable to a chance occurrence more than 5 times in 100?. Try Analysis of Variance (ANOVA). Part IV. Significantly Different:. Using Inferential Statistics. What you will learn in Chapter 13. What Analysis of Variance (ANOVA) is and when it is appropriate to use. The . Multivariate. Approach. One-Way. Cross-Species-Fostering. House mice onto house mice, prairie deer mice, or domestic Norway rats.. After weaning, tested in apparatus with access to tunnels scented like clean pine shavings, house mouse, deer mouse, or rat.. Questions (1). What are main effects in ANOVA? . What are interactions in ANOVA? How do you know you have an interaction? . What does it mean for a design to be completely crossed? Balanced? Orthogonal? . LM ANOVA 2. 2. Example -- Background. Bacteria -- effect . of temperature (10. o. C & 15. o. C) and relative humidity (20%, 40%, 60%, 80%) on growth rate (cells/d. ).. 120 . petri . dishes with a growth . ANOVA is comparison of means. Each possible value of a factor or combination of factor is a treatment.. The ANOVA is a powerful and common statistical procedure in the social sciences. It can handle a variety of situations.. ANOVA makes assumptions about error for significance tests. What are the assumptions?. What might happen (why would it be a problem) if the assumption of {normality, equality of error, independence of error} turned out to be false?.