PPT-Correlated-Samples ANOVA

Author : cheryl-pisano | Published Date : 2016-03-10

The Univariate Approach An ANOVA Factor Can Be Independent Samples Between Subjects Correlated Samples Within Subjects Repeated Measures Randomized Blocks Split

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Correlated-Samples ANOVA: Transcript


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. Andrea . Banino. & Punit . Shah . Samples . vs. Populations . Descriptive . vs. Inferential. William Sealy . Gosset. (‘Student’). Distributions, probabilities and P-values. Assumptions of t-tests. 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. Cohen’s . d. and Omega Squared. Jason R. Finley. Mon April 1. st. , 02013. http://. www.jasonfinley.com. /tools. ω. 2. DEAL WITH IT. Effect Sizes to use. Comparison of means . (. t. test):. Cohen’s . 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. Hao. Chai. Dereck. . Shen. Skull dataset. 138 skulls from 10 regions. Thickness was measured at 219 locations on each skull. Other variables in dataset:. Age of person (at time of death). Sex of person. Meng Yang. Phonetics Seminar. March 7, 2016. The Plan. Background: . C. ue weighting and cue shifting. Theories and predictions. My research questions. Methods (brace yourselves…). Results (yay!). Discussion. ANOVA. . (GLM 5). Chapter . 14. Mixed ANOVA. Mixed. :. 1 or more Independent variable uses the same . participants (repeated measures). 1 or more Independent variable uses different . participants (between subjects). Topic 8 – Analysis of Means. Normally Distributed. Not Normally Distributed. One sample vs. population. One sample t-test. Wilcoxon. Signed Rank. Two paired samples. Paired t-test. Difference then Signed Rank. ANOVA. Multiple Comparisons. Pairwise Comparisons and . Familywise. Error. . . fw. is the . alpha familywise. , the conditional probability of making one or more Type I errors in a family of . 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?. How does it work? . What is an F-ratio?. What is a grand mean?. What are the degrees of freedom for the F-ratio?. k-1, N-k. Post hoc tests. F-test in ANOVA is the so-called . omnibus test. . It tests the means globally. It says nothing about which particular means are different.. 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. 19. Introduction. (slide 1 of 3). The procedure for analyzing the difference between more than two population means is commonly called . analysis of variance. , or . ANOVA. .. There are two typical situations where ANOVA is used:. 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..

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