how to analyze your data

7/31/2019 How to Analyze Your Data

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Quick Overview: Types of DataQuick Overview: Types of Data Continuous

Ratio: e.g., height, weightRatio: e.g., height, weight

Interval: e.g., temperature, shoe sizeInterval: e.g., temperature, shoe size

Discrete/categorical

Ordinal: e.g., first, second, thirdOrdinal: e.g., first, second, third Nominal: e.g., #93, #13Nominal: e.g., #93, #13

How you use a scale determines the type of dataHow you use a scale determines the type of data!!

Example. #93, #13 on NHL jerseys isExample. #93, #13 on NHL jerseys is nominalnominal, but it, but it

could becould be ordinalordinal in your study if you chose to make the topin your study if you chose to make the top

player #1, and so on.player #1, and so on.


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What Type of Data Will You Collect?What Type of Data Will You Collect? QuestionnairesQuestionnaires

Interval rating scales: e.g.,Interval rating scales: e.g.,

Please indicate the extent to which you believe the defendantsPlease indicate the extent to which you believe the defendants claimclaim

Do not believe at allDo not believe at all 1 2 3 4 5 6 71 2 3 4 5 6 7 Believe completelyBelieve completely

Open-ended format: e.g.,

In your own words, please indicate if, and why, you believe thedefendants claim

CloseClose--ended format: e.g.,ended format: e.g.,

Please check the box that most closely matches why you believe thedefendants claim

No scientific evidence

Eye witness testimony

Alibi


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How Will You Analyze Your Data?How Will You Analyze Your Data?

Interval rating scales: means, continuous datameans, continuous data

TT--tests, ANOVA, correlation, regressiontests, ANOVA, correlation, regression

Open-ended format: many types of responses

(steer clear!) data needs to be coded for reliability Closed-ended format: frequency data

ChiChi--squaresquare


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TT--tests (experimental)tests (experimental) Independent measures,

One IV (discrete, two levels/groups), one DVOne IV (discrete, two levels/groups), one DV(continuous)(continuous)

Example:Example: Difference between men and women in levelsDifference between men and women in levels

of implicit selfof implicit self--esteemesteem Dependent (repeated) measures

One DV (continuous, measured twice)One DV (continuous, measured twice)

Example:Example: Difference in mens implicit selfDifference in mens implicit self--esteem levelsesteem levelsbefore and after a complex problembefore and after a complex problem--solving tasksolving task


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ANOVA (experimental)ANOVA (experimental) One-way ANOVA

One independent variable (discrete), one dependentOne independent variable (discrete), one dependent

variable (continuous)variable (continuous) Single main effect only (i.e., a difference in meansSingle main effect only (i.e., a difference in means

between at least two levels of an IV)between at least two levels of an IV)

Two-way ANOVATwo independent variables (discrete), one dependentTwo independent variables (discrete), one dependent

variable (continuous)variable (continuous)

Two main effects, one interactionTwo main effects, one interaction Definition:Definition:An interaction occurs when the influence ofAn interaction occurs when the influence of

one IV on the DV variable depends on the level of theone IV on the DV variable depends on the level of the

second IVsecond IV..


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Correlation/Regression (no causality)Correlation/Regression (no causality)

Correlation

Two continuous variables

Relationship between two variables

Regression One or morepredictors, one DV (continuous)

Used for predicting one variable from one or more other

variables


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ChiChi--square (mysquare (my favouritefavourite!)!)

ChiChi--square Goodnesssquare Goodness--ofof--Fit testFit test

One discrete variableOne discrete variableobserved vs. expectedobserved vs. expected

frequenciesfrequencies

ChiChi

--square Test of Independencesquare Test of Independence

Two discrete variablesTwo discrete variablesobserved vs. expectedobserved vs. expected

frequenciesfrequencies


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How to Enter DataHow to Enter Data

YouYou MUSTMUST identify your questionnairesidentify your questionnaires

with a codewith a code

ChooseChoose SHORTSHORT, but meaningful, variable, but meaningful, variable

names (no hyphens/spaces allowed)names (no hyphens/spaces allowed) Add label if necessaryAdd label if necessary

Add values (i.e., 1 = male, 2 = female)Add values (i.e., 1 = male, 2 = female)

Choose number of decimal spacesChoose number of decimal spaces


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Independent TIndependent T--TestTest

AnalyzeAnalyze

Compare meansCompare means

IndependentIndependent--Samples TSamples T--TestTest

Grouping Variable = IVGrouping Variable = IV

Define groups (enter 1, 2 where you have defined 1Define groups (enter 1, 2 where you have defined 1

and 2 in your dataset)and 2 in your dataset)

Test Variable = DVTest Variable = DV No options (e.g., Cohens d, charts) availableNo options (e.g., Cohens d, charts) available


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Repeated Measures TRepeated Measures T

AnalyzeAnalyze


PairedPaired--Samples TSamples T--TestTest

Paired Variables = prePaired Variables = pre

--/post/post

--test measurestest measures

No options (e.g., Cohens d, charts) availableNo options (e.g., Cohens d, charts) available


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OneOne--Way ANOVAWay ANOVA AnalyzeAnalyze


OneOne--wayway

ANOVAANOVA

Factor = IVFactor = IV

Dependent List =Dependent List =

DVDV

Post hoc (Post hoc (TukeyTukey))

No optionsNo options

AnalyzeAnalyze

General Linear ModelGeneral Linear Model

UnivariateUnivariate

Fixed Factor = IV (do notFixed Factor = IV (do not

use random factor)use random factor)

Dependent Variable = DVDependent Variable = DV

Post hoc =Post hoc =TukeyTukey PlotsPlots

Options: Estimates of effectOptions: Estimates of effect

sizesize


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CorrelationCorrelation

AnalyzeAnalyze

CorrelateCorrelate

BivariateBivariate

Variables = measuresVariables = measures

Default = PearsonDefault = Pearson

Use Spearman for ranked/ordinal dataUse Spearman for ranked/ordinal data

Options: Means,Options: Means, SDsSDs


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ChiChi--SquareSquare GoodnessGoodness--ofof--FitFit

AnalyzeAnalyze NonNon--parametricparametric

teststests

ChiChi--SquareSquare

Expected Values:Expected Values:leave at allleave at all

categories equalcategories equal

unless you have aunless you have a

good theory for whygood theory for why

they may bethey may be

differentdifferent

Test of IndependenceTest of Independence

AnalyzeAnalyze Descriptive StatisticsDescriptive Statistics

CrosstabsCrosstabs

RowRow: Add one variable: Add one variable

ColumnColumn: Add second variable: Add second variable

Statistics: ChiStatistics: Chi--SquareSquare

Cells: Observed & ExpectedCells: Observed & Expected

From results: Report PearsonFrom results: Report Pearson

ChiChi--Square from Chi SquareSquare from Chi Square

TestsTests


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Charts/PlotsCharts/Plots

Some tests include plotsSome tests include plotssome dontsome dont

If not, ChooseIf not, Choose

GraphsGraphs

Legacy DialogsLegacy DialogsWhichever type of chart you want to buildWhichever type of chart you want to build

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