PPT-Slide 1 Comparing Several Means: ANOVA

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Understand the basic principles of ANOVA Why it is done What it tells us Theory of oneway independent ANOVA Following up an ANOVA Planned contrastscomparisons Choosing

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Slide 1 Comparing Several Means: ANOVA: Transcript


Understand the basic principles of ANOVA Why it is done What it tells us Theory of oneway independent ANOVA Following up an ANOVA Planned contrastscomparisons Choosing contrasts Coding contrasts. Andrea . Banino. & Punit . Shah . Samples . vs. Populations . Descriptive . vs. Inferential. William Sealy . Gosset. (‘Student’). Distributions, probabilities and P-values. Assumptions of t-tests. 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. 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. The . Univariate. Approach. An ANOVA Factor Can Be. Independent Samples. Between Subjects. Correlated Samples. Within Subjects, Repeated Measures. Randomized Blocks, Split Plot. Matched Pairs if . k. 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?. Unweighted. MEANS ANOVA. Data Set “. Int. ”. Notice that there is an interaction here.. Effect of gender at School 1 is 155-110 = 45.. Effect of gender at School 2 is 135-120 = 15.. Weighted means. Lecture #. 28. . Thursday. , . December 1, . 2016. Textbook: . 16.1. • Generalize the two-sample t-test to more than two samples.. • Explain how testing equality of means can be rephrased as a test of variance (“Analysis of variance”).. (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. Comparing . & Ordering Fractions. Please . do not . be these people!. Comparing . & Ordering Fractions. Objective:. . 7.1.02. Essential Questions:. . How can I compare and order fractions?. Department of Applied Mathematics & Statistics. Stony Brook University. Review of . (the non-repeated measures) . ANOVA. 2. Review of ANOVA. The One-way ANOVA we have just learnt can test the equality of several population means.. 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.. 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.. Chapter 9. Review of Simulation-Based Tests. One proportion: . We created a null distribution by flipping a coin, rolling a die, or some computer simulation. . We then found where our sample proportion was in this null distribution.. 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?.

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