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Lecture Notes

by: Valerie Ho

Lecture Notes 209

Valerie Ho
GPA 3.53
research methods
Jacqueline Pickrell

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research methods
Jacqueline Pickrell
Class Notes
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This 4 page Class Notes was uploaded by Valerie Ho on Thursday October 8, 2015. The Class Notes belongs to 209 at University of Washington taught by Jacqueline Pickrell in Spring 2015. Since its upload, it has received 28 views. For similar materials see research methods in Psychlogy at University of Washington.


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Date Created: 10/08/15
Psych209 Lecture and Section Chapter 9 Experimental and Control Conditions Participants in an experimental condition are exposed to a treatment whereas participants in a control condition do not receive the treatment Key terms 0 Factors IVs 0 Levels categories that comprise the factor makes the IV vary 0 Conditions groups that are created by combinations of different levels of IV 0 Betweensubject design different groups of participants contribute data for different levels of the IV 0 Withinsubject same participants contribute data to all levels of the IV Four types of singlefactor designs Betweensubjects Independent groups Matched groups Nonequivalent groups Withinsubjects Repeated measures Factorial Designs Complex design An experiment in which 2Vs are studies simultaneously Factorial design Involved all combinations of at least two values of 2 IV A type of complex design in which every level of an IV is crossed with every level of every other IV Factorial matrix LevelBl LevelBZ Level A1 A181 A182 Level A2 A2 Bl A2 82 Identifying Factorial Designs 1 Number identi es IVs levels conditions of numbers indicates how many IVs Each individual number indicates of levels in each IV Multiply to nd of conditions For example 2 x 2 factorial design quot quot 2 levels of IV of conditions 2 x 2 4 Main effects amp interactions 0 Main effects Overall effect of an IV ignoring the other levels of IVs o Interactions When the in uence of one AV on the DV differs in directionstrength depending on the level of another IV Determining if there is a main effect Calculate quotrow and column meansquot ie comparing the average of each level of the IV If the means of the levels of a factor differ signi cantly from one another there is a main effect for that factor ie recognize main effect by seeing if there s a mean difference across the various levels of IV In simple words on a line graph Compare the XaXis averages and see if they re the same usually there 5 two I V5 in the Xaxis Determining if there is an interaction 1 See if there s difference between cell values for each IV level Calculations AlBlAlBZ Then AZBlAZBZ If there s a differences between the two scores then there s an interaction sign matters ve signed ve signed 2 Looking at line graphs When the difference between the two ends of the data line is the same then there is NO interaction Thus if the lines are parallel then there s no interaction Section 51215 2 x 2 designs A review A factorial design with 2 IV each with 2 levels Three possible results 0 Two main effects Differences exist between levels of each IV 0 One Interaction The effect of 1st IV differs depending on the level of the 2nCI IV Endpoint centers for a main effect take average of the end points of both lines Youtube review of main effects and interaction httpswwwyoutubecomwatchvOE46w0RqmOA Lecture 51315 Example practice 1 2x2 Participants are randomly assigned one of the four conditions in a 2x2 experiment IV1 Exercise IV2 Caffeine DV Mena number of calories consumedday No Exercise Exercise No Caffeine 2100 2100 Caffeine 2300 2300 o Is there a main effectfor Exercise NO because the total of the column for exercise is the same 21002300 4400 Caffeine YES because the mean for the rows are different 21002100 VS 23002300 On average people that consumed caffeine consumed more calories per day than those that had not consumed caffeine regardless of their amount of exercise o Is there an interaction NO 210021000 AND 230023000 row OR column difference When there s an interaction then researchers present the interaction HW 4 Research Proposal quotIE Two le with 2 level each At least one manipulated In The Vs must interact with each other SingleFactor VS Factorial Design With a factorial design you know that the course format matters but only for a certain time of day Factorial designs can be more informative Do gender role stereotypes about an occupation in uence the way we process words in sentences Using ERP to study word processing Eventrelated potentials ERPs are scalprecorded voltage changes that are timelocked to an event ie presentation of a word Varieties of Factorial Designs All BSD Independent Groups matched groups nonequivalent groups All WSD Repeated measures Unique to factorial designs Both between and within le can be present in a factorial design Mixed factorial design at least one IV is BSD and at least one other is WSD ln MFD knowing how many Ps you need to recruit is tricky Firstly BSD need enough Ps to ll al cells in even numbers Low efficacy when participants have limited options in an experiment when they are manipulated but cannot control the situation by themselves Unique to factorial designs Some betweensubjects factorials include both a manipulated IV and subject IV P X 5E factorial design Person by Situation design pg 273274 P subject IV S manipulated IV aka environment 0 It is popular because they combine correlational P and experimental research S traditions Can we draw conclusions about causality from P x S designs 0 Subject variable P NO 0 IV S YES


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