Lecture 15 Psyc 300A. Example: Movie Preferences MenWomenMean Romantic364.5 Action745.5 Mean55.

Slides:



Advertisements
Similar presentations
Statistics for the Social Sciences
Advertisements

Chapter Fourteen The Two-Way Analysis of Variance.
PSY 307 – Statistics for the Behavioral Sciences
Dr. Sinn, PSYC301, The joy of 1-way ANOVA1 Unit 3 Outline Day 1: Introduce F Return Tests (20) Power (20) Matching variance with data, ranking Fs (20)
Basic Data Analysis for Quantitative Research
One-Way Between Subjects ANOVA. Overview Purpose How is the Variance Analyzed? Assumptions Effect Size.
Conceptual Review Conceptual Formula, Sig Testing Calculating in SPSS
Lecture 13 Psyc 300A. Review Confounding, extraneous variables Operational definitions Random sampling vs random assignment Internal validity Null hypothesis.
Factorial ANOVA 2-Way ANOVA, 3-Way ANOVA, etc.. Factorial ANOVA One-Way ANOVA = ANOVA with one IV with 1+ levels and one DV One-Way ANOVA = ANOVA with.
Intro to Statistics for the Behavioral Sciences PSYC 1900
POST HOC COMPARISONS What is the Purpose?
Jeopardy! One-Way ANOVA Correlation & Regression Plots.
Lecture 14 Psyc 300A. Review Operational definitions Internal validity Threats to internal validity Type I and type II errors.
Lecture 16 Psyc 300A. What a Factorial Design Tells You Main effect: The effect of an IV on the DV, ignoring all other factors in the study. (Compare.
Two Groups Too Many? Try Analysis of Variance (ANOVA)
Complex Design. Two group Designs One independent variable with 2 levels: – IV: color of walls Two levels: white walls vs. baby blue – DV: anxiety White.
PSY 307 – Statistics for the Behavioral Sciences Chapter 16 – One-Way ANOVA (Cont.)
Intro to Statistics for the Behavioral Sciences PSYC 1900
Factorial Designs More than one Independent Variable: Each IV is referred to as a Factor All Levels of Each IV represented in the Other IV.
Intro to Statistics for the Behavioral Sciences PSYC 1900 Lecture 14: Factorial ANOVA.
PSY 307 – Statistics for the Behavioral Sciences Chapter 19 – Chi-Square Test for Qualitative Data Chapter 21 – Deciding Which Test to Use.
Comparing Several Means: One-way ANOVA Lesson 14.
Lecture 13: Factorial ANOVA 1 Laura McAvinue School of Psychology Trinity College Dublin.
Introduction to Analysis of Variance (ANOVA)
Repeated Measures ANOVA Used when the research design contains one factor on which participants are measured more than twice (dependent, or within- groups.
Understanding the Two-Way Analysis of Variance
Statistics for the Social Sciences Psychology 340 Fall 2013 Thursday, November 21 Review for Exam #4.
Repeated ANOVA. Outline When to use a repeated ANOVA How variability is partitioned Interpretation of the F-ratio How to compute & interpret one-way ANOVA.
ANOVA Chapter 12.
Part IV Significantly Different: Using Inferential Statistics
Lecturer’s desk INTEGRATED LEARNING CENTER ILC 120 Screen Row A Row B Row C Row D Row E Row F Row G Row.
Review of ANOVA PSY 340 Fall 2013 Thursday, October 31.
Chapter 11 HYPOTHESIS TESTING USING THE ONE-WAY ANALYSIS OF VARIANCE.
Comparing Several Means: One-way ANOVA Lesson 15.
Analysis of Variance (Two Factors). Two Factor Analysis of Variance Main effect The effect of a single factor when any other factor is ignored. Example.
A Repertoire of Hypothesis Tests  z-test – for use with normal distributions and large samples.  t-test – for use with small samples and when the pop.
© Copyright McGraw-Hill CHAPTER 12 Analysis of Variance (ANOVA)
Slide 1 Two-Way Independent ANOVA (GLM 3) Prof. Andy Field.
Psychology 301 Chapters & Differences Between Two Means Introduction to Analysis of Variance Multiple Comparisons.
Lab 5 instruction.  a collection of statistical methods to compare several groups according to their means on a quantitative response variable  Two-Way.
 Slide 1 Two-Way Independent ANOVA (GLM 3) Chapter 13.
Chapter 10: Analyzing Experimental Data Inferential statistics are used to determine whether the independent variable had an effect on the dependent variance.
1 Analysis of Variance ANOVA COMM Fall, 2008 Nan Yu.
Remember You were asked to determine the effects of both college major (psychology, sociology, and biology) and gender (male and female) on class attendance.
12: Basic Data Analysis for Quantitative Research.
ANOVA: Analysis of Variance.
Chapter 13 - ANOVA. ANOVA Be able to explain in general terms and using an example what a one-way ANOVA is (370). Know the purpose of the one-way ANOVA.
Analysis of Variance (One Factor). ANOVA Analysis of Variance Tests whether differences exist among population means categorized by only one factor or.
1 Analysis of Variance (ANOVA) Educational Technology 690.
Mixed ANOVA Models combining between and within. Mixed ANOVA models We have examined One-way and Factorial designs that use: We have examined One-way.
ONE-WAY BETWEEN-GROUPS ANOVA Psyc 301-SPSS Spring 2014.
ANOVAs.  Analysis of Variance (ANOVA)  Difference in two or more average scores in different groups  Simplest is one-way ANOVA (one variable as predictor);
Research Methods and Data Analysis in Psychology Spring 2015 Kyle Stephenson.
Quiz 11  Analysis of Variance (ANOVA)  post hoc tests.
Social Science Research Design and Statistics, 2/e Alfred P. Rovai, Jason D. Baker, and Michael K. Ponton Between Subjects Analysis of Variance PowerPoint.
Smith/Davis (c) 2005 Prentice Hall Chapter Fifteen Inferential Tests of Significance III: Analyzing and Interpreting Experiments with Multiple Independent.
Handout Eight: Two-Way Between- Subjects Design with Interaction- Assumptions, & Analyses EPSE 592 Experimental Designs and Analysis in Educational Research.
Research Methods and Data Analysis in Psychology Spring 2015 Kyle Stephenson.
Simple ANOVA Comparing the Means of Three or More Groups Chapter 9.
F-Tables & Basic Ratios. Outline of Today’s Discussion 1.Some F-Table Exercises 2.Introduction to Basic Ratios [Between-Subject ANOVA] 3.Independent Samples.
Educational Research Inferential Statistics Chapter th Chapter 12- 8th Gay and Airasian.
Дисперсионный анализ ANOVA
ANOVA with SPSS Recap.
Two way ANOVA with replication
Two way ANOVA with replication
Statistics for the Social Sciences
Interactions & Simple Effects finding the differences
Main Effects and Interaction Effects
Analysis of Variance: repeated measures
Exercise 1 Use Transform  Compute variable to calculate weight lost by each person Calculate the overall mean weight lost Calculate the means and standard.
Presentation transcript:

Lecture 15 Psyc 300A

Example: Movie Preferences MenWomenMean Romantic364.5 Action745.5 Mean55

What a Factorial Design Tells You Main effect: The effect of an IV on the DV, ignoring all other factors in the study. (Compare means of different levels of IV, while ignoring [collapsing across] other IVs [ i.e., compare marginal means]) Interaction effect: When the effect of one IV on a DV differs depending on the level of a second IV. Interpret the interaction first

Group Exercise: Main Effects and Interactions Any questions from p.205 in book?

Example: Psychotherapy Outcome PrePostMarginal Mean Cognitive No Tx20 Marginal Mean 2015

Group Activity For each graph, decide whether there are main effects for each variable and an interaction.

Group Activity: Main Effects and Interactions Make graphs of the following situations: Study 1  Study 2  Study 3  Study 4  Var AVar BAxB interaction p <.05 n.s. p <.05 n.s.p <.05 n.s. p <.05

Factorial Designs: Naming Conventions The first number is the number of levels in first IV, second number is number of levels in second IV, etc. 2 x 2 2 x 3 2 x 2 x 3 Between-subjects, repeated measures (within), mixed

A 2 x 3 Interaction

Analysis of Variance (ANOVA) Test statistic for ANOVA is F Is related to t-test ANOVA is for multiple levels of IV and multiple IVs MS between F = MS within It compares the amount of variability between groups to amount within groups

ANOVA Source (or Summary) Table _______________________________________ Source df SS MS F. Between groups Within groups Total _______________________________________

Interpreting the F statistic (ANOVA) Hand calculations –Calculate F (this is F obtained ). –Compare value with F in table (Table B.3. This is F critical ). To do this need to know alpha and df. –If F obtained > F critical, a significant effect. In SPSS –Look at source (summary) table –Effects with significance values less than.05 are significant.

ANOVA (one way) Example Do preschoolers benefit from extra practice in language skills? Groups: 1=5hrs; 2=10 hrs; 3=20 hrs

Oneway ANOVA: SPSS Output

Post hoc comparisons When there are more than two conditions, a significant F-test tells you that at least two means are different, but not which ones To discover which are different, we use post hoc comparisons Some of these include Scheffe, Newman-Keuls, Duncan, Tukey tests

SPSS: Factorial ANOVA, All Between- Subjects IVs (Weight loss data) Female trainer Female trainer Male trainer Male trainer Female client Male client Female client Male client

SPSS Data File: Weight Loss Study

SPSS Weight Loss Study Plot

SPSS Output File: Weight Loss Study