~Drowning in Data~ SPSS Data Analysis 3/26/12
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Transcript of ~Drowning in Data~ SPSS Data Analysis 3/26/12
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~Drowning in ~Drowning in Data~Data~
SPSS Data AnalysisSPSS Data Analysis
3/26/123/26/12Sumiko Takayanagi, Ph.D.
Sr. StatisticianUCLA School of Nursing
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Today’s PresentationToday’s Presentation SPSS Environment SPSS Environment
Review of SPSS BasicsReview of SPSS Basics
Inferential Statistics in SPSS Inferential Statistics in SPSS Independent t-testIndependent t-test Two-Way Analysis of VarianceTwo-Way Analysis of Variance Multiple RegressionMultiple Regression
ConclusionConclusion
ReferencesReferences
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Features of SPSSFeatures of SPSS Originally developed for the people in Originally developed for the people in
Social Science Areas, therefore, no heavy Social Science Areas, therefore, no heavy programming background requiredprogramming background required
Designed as User Friendly and has Pull Designed as User Friendly and has Pull Down Menus to Execute Statistical Down Menus to Execute Statistical CommandsCommands
Ability to do Data Management & Ability to do Data Management & ManipulationsManipulations
Ability to Store Programs & Produce Ability to Store Programs & Produce Reports/GraphsReports/Graphs
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SPSS Program FlowSPSS Program Flow
Data Modification/
Transformation
Pull-DownMenu
SPSSDataFile
OutsideData
Source
RawData
Data Analysis
Importing
Direct E
ntry
SyntaxMenu
OR
(Data Steps) (Analysis Steps)
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Data View Window - Data Entry Site - Data Entry Site(Columns=Variables, Rows=Cases)(Columns=Variables, Rows=Cases)
Title bar
Tool bar
Data View window
Information barPull-down Menu bar
Active cell Action bar
VariableNames
Help Menu
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Variable View WindowData Definition SiteData Definition Site
64 CharactersMax, No spaceBetween Beg letter, @, #, or $
Variable Description
Length
Numeric,String, &Others
Click here to see this view
Value Code
Description
# of Decimals
Missing value
Description
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1. OK - results/action will be executed
OK PasteVS.
buttons
Before we Before we see see
Examples…Examples… <Output File>
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1.Hit Paste to obtain Syntax Window
2. Run Syntaxto obtain the results in theOutput Window
<Syntax File>
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Example - School Data Example - School Data Raw DataRaw Data
Subject 1Subject 1 Subject #Subject # (1)(1) FemaleFemale (1)(1) IntensiveIntensive (1)(1) Reading (90)Reading (90) Math Math (67)(67)
Subject 2Subject 2 Subject # Subject # (2)(2) FemaleFemale (1)(1) ModerateModerate (2)(2) Reading Reading (72)(72) Math Math (46)(46)
Subject 3Subject 3 Subject # Subject # (3)(3) MaleMale (0)(0) BasicBasic (3)(3) ReadingReading (41)(41) MathMath (73)(73)
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School DataSchool DataVariable ViewVariable View
Variable View Activated
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School DataSchool DataCompleted Dataset – Data Completed Dataset – Data
ViewView
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School DataSchool DataCompleted Dataset – Completed Dataset –
Variable ViewVariable View
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Importing Excel Data file Importing Excel Data file to SPSSto SPSS
2. Go to File Menu
3. Click “Read Text Data”
4. Click Files of type to Excel & choose Excel file
5. Hit Open
6. Check Worksheet #, Variable on the 1st row, & Hit OK
1. Open the SPSS Data file
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School DataSchool DataCompleted Dataset – Data Completed Dataset – Data
ViewView
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Click to Obtain Click to Obtain Data File InformationData File Information
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Variable InformationVariable Information
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Value Code InformationValue Code Information
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Basic Statistical Basic Statistical Methods Methods
Independent t-testIndependent t-test Two-Way ANOVATwo-Way ANOVA Multiple Multiple
Regression Regression
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AssumptiAssumptionsons
1. 1. NormalityNormality
2. Variance 2. Variance EqualityEquality
3. 3. IndependenIndependencece
# of # of VariablesVariables
CharacteristiCharacteristicscs
School DataSchool Data
N=100N=100
Dependent = Dependent = 11
ContinuousContinuous Math ScoreMath Score
Range of 0-Range of 0-100100
Independent Independent = 1= 1
CategoricalCategorical
2-levels2-levelsGenderGender
Independent t-testIndependent t-test– Is there a significant difference – Is there a significant difference
between 2 groups?between 2 groups?
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How to calculate t-How to calculate t-value?value?
Mean Mean DifferenceDifference
Group Group VariabilityVariability
t-value=
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t-testt-test
MediumVariability
HighVariability
LowVariability
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Independent t-testIndependent t-test
1. Go to Analyze.
2. Choose Compare Means.
3. Choose IndependentSamples t Test.
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t-testt-test
1. Choose Dependent& Independent Variables.
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Variance Equality Test t - statistics
t = Z1 – Z2 = 63.20 – 54.10 = 9.093 = 3.295 SD1
2 + SD22 (13.914)2 +(13.064)2 2.760
N1 N2
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t = Mean Diff Std. Error Diff
Dependent Variable
Descriptives & Analysis
Independent Variable
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Conclusion & Chart
There is a There is a significansignificant t difference difference in math in math ability ability between between males and males and females. females. Males Males performeperformed better d better than than females.females.
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AssumptiAssumptionsons
1. 1. NormalityNormality
2. Variance 2. Variance EqualityEquality
3. 3. IndependenIndependencece
# of # of VariablesVariables
CharacteristiCharacteristicscs
School DataSchool Data
N=100N=100
Dependent = Dependent = 11
ContinuousContinuous Math ScoreMath Score
0-1000-100
Independent Independent >1>1
Categorical-Categorical-
2 or more 2 or more levelslevels
GenderGender
Program Program TypeType
Factorial ANOVAFactorial ANOVA– Is there any main or the – Is there any main or the
interaction effects?interaction effects?
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2 x 3 Factorial ANOVA2 x 3 Factorial ANOVADesign DiagramDesign Diagram
GenderGender
ProgramProgram
MaleMale FemaleFemale
MildMild 56, 86, 70, 56, 86, 70, 69, …..69, …..
55, 72, 67, 55, 72, 67, 48, …..48, …..
ModerateModerate 86, 59, 67, 86, 59, 67, 80, …..80, …..
63, 78, 55, 63, 78, 55, 46, …..46, …..
IntensiveIntensive 89, 92, 86, 89, 92, 86, 71, ….. 71, …..
72, 76, 54, 72, 76, 54, 56, …..56, …..
Math Test Scores
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2-Way Factorial ANOVA2-Way Factorial ANOVA
1.Go to General Linear Model & choose Univariate.
2. Choose One Dependent & Two Independent Variables.
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Factorial ANOVA Factorial ANOVA (2x3)(2x3)
1. Freq of IV and Raw Means
2. Equality of Variance Test
Descriptives
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Factorial ANOVAFactorial ANOVA
Main Effects &Interaction
Main Analysis
Results:Results: Main effect – Sig. difference in Main effect – Sig. difference in gendergender and in and in
program typeprogram type.. Interaction – Sig. interaction between gender Interaction – Sig. interaction between gender
and program type. and program type.
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Factorial ANOVAFactorial ANOVA
Scheffe & LSD Methods
MultipleComparison
Sig. Differentlevel
Which levels are actuallyDifferent ??
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Factorial ANOVAFactorial ANOVA
Significant Effects Significant Effects Males performed Males performed
better than females.better than females. Students in the Students in the
Intensive program Intensive program performed better performed better than in the Mild than in the Mild program.program.
Males in the Males in the Intensive program Intensive program performed better performed better than in other than in other programs, but no programs, but no performance performance difference in females. difference in females.
Conclusion
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AssumptioAssumptionsns
1. 1. NormalityNormality
2. 2. Variance Variance EqualityEquality
3. 3. IndependeIndependencence
4. Linear4. Linear
RelationshRelationshipip
# of # of VariablesVariables
CharacteristiCharacteristicscs
Health Survey DataN=100N=100
Dependent Dependent =1=1
ContinuousContinuous LDL ValueLDL Value
0-2000-200
Independent Independent > 1> 1
Continuous Continuous or or Dichotomous Dichotomous (0 or 1) (0 or 1) VariablesVariables
HT, WT, BMI, HT, WT, BMI, & &
ExerciseExercise
Multiple RegressionMultiple Regression – Which IVs can predict the DV and to estimate – Which IVs can predict the DV and to estimate
the effects of these variables on DV?the effects of these variables on DV?
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Multiple Regression Multiple Regression DiagramDiagram
LDL
HT
WT
BMI
Exercise
DV
IV
All 4 IVs are predicting LDL
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Health Survey Data of N=100
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Multiple RegressionMultiple Regression
1.Choose Regression
2. Choose Linear Regression
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2. Choose Statistics you need.
3. Choose Residual Plots.
1. Choose DV, IV, & Method.
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Descriptives& Correlation
Tables
CorrelationCoefficients & correspondingp-values.
DescriptiveStats.
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Main Analysis
R=r between pred and observ value of the DV
B=Reg Coefficient
Global test to see if any coefficient is different from “0”
R2=how much of the variability in the outcome is accounted
for by the predictors (regression sum of squared/total sum of squares)
Adj. R Sq=Adj for the # of Parameters in the model
Beta=Stdized. Reg Coefficient.Something is Wrongif Beta >1!!
t & Sig=IV predictability
Tolerance &VIF
Partial/PartCorrelations
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Residual Normality Linearity and Equal Variance & residual independence
Residual Analysis
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IVs explain about IVs explain about 40% of the 40% of the variability of LDL variability of LDL level.level.
The significant The significant predictors of LDL predictors of LDL were BMI and Hrs of were BMI and Hrs of Exercise.Exercise.
The collinearity The collinearity statistics didn’t statistics didn’t show exceptionally show exceptionally large large multicollinearity multicollinearity among predictors. among predictors.
Assumptions of Assumptions of residual normality residual normality and equal variance and equal variance were met.were met.
Conclusion Multiple Multiple
RegressionRegression
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Key ConceptsKey Concepts
Statistical Models depend on the Statistical Models depend on the theory and data. Choose your model theory and data. Choose your model wisely to see if it can answer your wisely to see if it can answer your research questions.research questions.
Check Assumptions. Model Check Assumptions. Model conclusions may not be valid unless conclusions may not be valid unless the assumptions were met. If not, the assumptions were met. If not, use appropriate corrections, do data use appropriate corrections, do data transformations, or even use other transformations, or even use other statistical methods.statistical methods.
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ConclusionsConclusions
Statistical judgments come Statistical judgments come into our daily lives. Statistics into our daily lives. Statistics are more than mathematical are more than mathematical calculations or scientific calculations or scientific research, but they are the research, but they are the way of logical thinking…way of logical thinking…
Thank youThank you