PDF-N way Anova cornfield tukey rules

x0102x0204x0105 x1516x0A0Dx170Box1018MF1ox1D11Hx1B10o Ex1920x0F1Dbx211FwW x1516fx0D17cox1819Fx1B1Cx091DbHx0913 x0102x0204x0105. Andrea . Banino. & Punit . Shah . Samples . vs. Populations . Descriptive . vs. Inferential. William Sealy . Gosset. (‘Student’). Distributions, probabilities and P-values. Assumptions of t-tests. Analysis by SAS. Interaction Plot . by Excel. The Design. Type of Crime: Burglary or Swindle. Culture of Defendant: American or Chinese. Sex of Juror: Female or Male. DV: Recommended length of sentence. 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. 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 . 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. 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. 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 . 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. 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.. 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..  = 0.05. ANOVA: Graphical. Example: ANOVA terms. Treatment 1. Treatment 2. Treatment. 3. 1. y. 11. = 48. y. 21. = 40. y. 31. = 39. 2. y. 12. = 39. y. 22. = 48. y. 32. = 30. 3. y. 13. = 42. 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?.