ANOVA Within-Subject

ANOVA Within-Subject - ANOVA: Introduction 1. ANOVA is much...

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1 1. ANOVA is much like a t-test. It compares sample means to see if they are significantly different from each another. 2. ANOVA is unlike t-test, for it can compare more than two sample means and also many independent variables. 3. ANOVAs do not allow for directional alternative hypotheses, like t-tests do: H 0 : μ 1 = μ 2 3 H 1 : μ 1 ≠ µ 2 ≠µ 3 ANOVA: Introduction 1 4. ANOVA needs a follow-up test (post-hoc test ) , if the null hypothesis is rejected to find exactly which pairs of means are different from one another. 5. ANOVA is said to be a robust technique when the following assumptions are met (these assumptions can be violated to some extent). 1. Normal distribution 2. Homogeneity of variance 3. Independent observations 4. Data: interval or ratio Introduction 2 Problem An investigator selected a group of ten volunteers and tested three conditions of Word-Color Compatibility viz., incongruent condition (word-color incompatible) congruent (word-color compatible) and control (nonword-color association) by measuring reaction time (ms). She wanted to know if there were significant differences among the reaction times of the three conditions. If they were, was her hypothesis supported? 3
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2 Independent variable Word-Color Compatibility Conditions Incongruent, congruent and control Dependent variable Reaction time (ms) Design of the study? Single factor within-subject design 4 Participants Control Congruent Incongruent 1 1014 1077 1230 2 1092 1093 1387 3 962 884 1074 4 1115 1184 1332 5 846 900 1213 6 897 875 1139 7 971 1009 1186 8 1044 1069 1164 9 1144 1158 1285 10 1060 1101 1544 Mean 1015 1035 1255 Word-Color compatibility 1015 1035 1255 900 1000 1100 1200 1300 1400 Control Congruent Incongruent Word-Color Compatibility
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ANOVA Within-Subject - ANOVA: Introduction 1. ANOVA is much...

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