PPT-Regression Part II One-factor ANOVA

Another dummy variable coding scheme Contrasts Multiple comparisons Interactions One factor Analysis of variance Categorical Explanatory variable Quantitative Response variable p categories groups. Andrea . Banino. & Punit . Shah . Samples . vs. Populations . Descriptive . vs. Inferential. William Sealy . Gosset. (‘Student’). Distributions, probabilities and P-values. Assumptions of t-tests. Methods for Dummies. Isobel Weinberg & Alexandra . Westley. Student’s t-test. Are these two data sets significantly different from one another? . William Sealy Gossett. Are these two distributions different?. AMS 572 Group 5. Outline. Jia. Chen: Introduction of repeated measures ANOVA. Chewei. Lu: One-way repeated measures . Wei Xi: Two-factor repeated measures. Tomoaki. Sakamoto : Three-factor repeated measures. Methods for Dummies. Isobel Weinberg & Alexandra . Westley. Student’s t-test. Are these two data sets significantly different from one another? . William Sealy Gossett. Are these two distributions different?. Andrea . Banino. & Punit . Shah . Samples . vs. Populations . Descriptive . vs. Inferential. William Sealy . Gosset. (‘Student’). Distributions, probabilities and P-values. Assumptions of t-tests. Methods for Dummies. Isobel Weinberg & Alexandra . Westley. Student’s t-test. Are these two data sets significantly different from one another? . William Sealy Gossett. Are these two distributions different?. Andrea . Banino. & Punit . Shah . Samples . vs. Populations . Descriptive . vs. Inferential. William Sealy . Gosset. (‘Student’). Distributions, probabilities and P-values. Assumptions of t-tests. Understand the basic principles of ANOVA. Why it is done?. What it tells us?. Theory of one-way independent ANOVA. Following up an ANOVA. :. Planned contrasts/comparisons. Choosing contrasts. Coding contrasts. ‘People can be divided into two classes: . Those who go ahead and do something, . and those who sit still and inquire, . 'Why wasn't it done the other way?’’. – Oliver Wendell Holmes, American Physician, Writer, . Variance. Lecture . /slide deck produced by Saul Greenberg, University of Calgary, Canada. . Notice: some material in this deck is used from other sources without permission. Credit to the original source is given if it is known,. 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 . Two-way ANOVA Factor Level Means Study Cells defined b y combinations of t w o or more discrete f actors All o ws ef f ects to be decomposed into main ef f ects and inte r actions Model assumptions remain unchanged 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.. Cohen Chapter 15. ANOVA. “The biggest job we have is to teach a newly hired employee how to . fail. intelligently. We have to train him to experiment over and over and to keep on trying and failing until he learns what will work.”.