[Two alternative types of formats are used here to illustrate some possible styles]

Size: px
Start display at page:

Download "[Two alternative types of formats are used here to illustrate some possible styles]"

Transcription

1 EXMPLE OF SPSS OUTPUT WITH CLSS SHRED DTBSE [SPSS commends are highlighted in yellow]. Simple frequency distributions Means (+nova) Simple correlations Reliability analysis for scales Linear Regressions Mapping graph Scatterplot Interactive 3-d rotating Thumbnail Scatterplots..... GET FILE='C:\shared database.sav'.. Simple frequency distributions FREQUECIES VRIBLES=society typedemo /ORDER= LYSIS. SOCIETY Type of Society (Classified based on the HDI 998) Valid Postindustrial Industrial grarian Cumulative Frequency Percent Valid Percent Percent TYPEDEMO Type of State (Classified based on the FH ) Valid Older democracy ewer democracy Semi-democracy on-democratic Cumulative Frequency Percent Valid Percent Percent [Two alternative types of formats are used here to illustrate some possible styles]

2 EXMPLE OF SPSS OUTPUT WITH CLSS SHRED DTBSE 2. Simple tables CROSSTBS /TBLES=society BY typedemo /FORMT= VLUE TBLES /STTISTIC=GMM /CELLS= COUT ROW COLUM. Crosstabs OCIETY Type of Society (Classified based on the HDI 998) * TYPEDEMO Type of State (Classified based on th FH ) Crosstabulation SOCIETY Type of Society (Classified based on the HDI 998) Postindustrial Industrial grarian Count Row % Column % Count Row % Column % Count Row % Column % Count Row % Column % TYPEDEMO Type of State (Classified based on the FH ) Older ewer Semi-de on-dem democracy democracy mocracy ocratic % 00.0% 55.0%.5% % 37.5% 23.4% 20.3% 00.0% 30.0% 55.8% 3.9% 2.0% 33.3% % 7.9% 30.2% 46.2% 00.0% 5.0% 44.2% 68.% 79.0% 55.2% % 22.4% 24.5% 32.3% 00.0% 00.0% 00.0% 00.0% 00.0% 00.0% Ordinal by Ordinal of Valid Cases Gamma a. ot assuming the null hypothesis. Symmetric Measures symp. Value Std. Error a pprox. T b pprox. Sig b. Using the asymptotic standard error assuming the null hypothesis. 2

3 EXMPLE OF SPSS OUTPUT WITH CLSS SHRED DTBSE 3. Means (+nova) MES TBLES=pstable rulelaw goveff corrupt BY typedemo /CELLS ME COUT STDDEV /STTISTICS OV. Means Report TYPEDEMO Type of State (Classified based on the FH ) Older democracy ewer democracy Semi-democracy on-democratic Mean Std. Deviation Mean Std. Deviation Mean Std. Deviation Mean Std. Deviation Mean Std. Deviation PSTBLE GOVEFF Political RULELW Government CORRUPT Stability Rule of Law Efficiency Corruption

4 EXMPLE OF SPSS OUTPUT WITH CLSS SHRED DTBSE OV Table Sum of Squares df Mean Square F Sig. PSTBLE Political Stability * TYPEDEMO Type of State (Classified based on the FH ) Between Groups Within Groups (Combined) RULELW Rule of Law * TYPEDEMO Type of State (Classified based on the FH ) Between Groups Within Groups (Combined) GOVEFF Government Efficiency * TYPEDEMO Type of State (Classified based on the FH ) Between Groups Within Groups (Combined) CORRUPT Corruption (World Bank) * TYPEDEMO Type of State (Classified based on the FH ) Between Groups Within Groups (Combined) Measures of ssociation PSTBLE Political Stability * TYPEDEMO Type of State (Classified based on the FH ) RULELW Rule of Law * TYPEDEMO Type of State (Classified based on the FH ) GOVEFF Government Efficiency * TYPEDEMO Type of State (Classified based on the FH ) CORRUPT Corruption (World Bank) * TYPEDEMO Type of State (Classified based on the FH ) Eta Eta Squared

5 EXMPLE OF SPSS OUTPUT WITH CLSS SHRED DTBSE 4. Simple correlations CORRELTIOS /VRIBLES=income98 pstable rulelaw goveff corrupt /PRIT=TWOTIL OSIG /MISSIG=PIRWISE. Correlations Correlations ICOME98 GDP 998 (UDP) Pearson Correlation Sig. (2-tailed) ICOME98 GDP 998 (UDP) PSTBLE Political Stability RULELW Rule of Law GOVEFF Government Efficiency CORRUPT Corruption PSTBLE Political Stability Pearson Correlation Sig. (2-tailed).659** RULELW Rule of Law Pearson Correlation Sig. (2-tailed).767**.880** GOVEFF Government Efficiency CORRUPT Corruption Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed) **. Correlation is significant at the 0.0 level (2-tailed)..760**.797**.888** **.749**.875**.927**

6 EXMPLE OF SPSS OUTPUT WITH CLSS SHRED DTBSE 5. Reliability analysis for scales RELIBILITY /VRIBLES=pstable rulelaw goveff corrupt /FORMT=OLBELS /SCLE(LPH)=LL/MODEL=LPH /STTISTICS=DESCRIPTIVE SCLE /SUMMRY=TOTL. Reliability ****** Method (space saver) will be used for this analysis ****** R E L I B I L I T Y L Y S I S - S C L E ( L P H ) Mean Std Dev Cases. PSTBLE RULELW GOVEFF CORRUPT of Statistics for Mean Variance Std Dev Variables SCLE Item-total Statistics Scale Scale Corrected Mean Variance Item- lpha if Item if Item if Item Deleted Deleted Correlation Deleted PSTBLE RULELW GOVEFF CORRUPT Reliability Coefficients of Cases = 49.0 of Items = 4 lpha =

7 EXMPLE OF SPSS OUTPUT WITH CLSS SHRED DTBSE 6. Linear Regressions REGRESSIO /MISSIG LISTWISE /STTISTICS COEFF OUTS R OV /CRITERI=PI(.05) POUT(.0) /OORIGI /DEPEDET corrupt /METHOD=ETER income98 tot_pop africa asia ceurope meast nam sam scan weuro. Regression Model Model Summary djusted R Std. Error of R R Square Square the Estimate.88 a a. Predictors: (Constant), WEURO Western Europe (dummy var from region), TOT_POP Population 997, (UDP), SC Scandinavia (dummy var from region), M orth merica (dummy var from region), MEST Middle East (dummy var from region), CEUROPE Central and Eastern Europe (dummy var from region), SM South merica (dummy var from region), SI sia (dummy variable from region), ICOME98 GDP 998 (UDP) Model Regression Residual OV b Sum of Squares df Mean Square F Sig a a. Predictors: (Constant), WEURO Western Europe (dummy var from region), TOT_POP Population 997, (UDP), SC Scandinavia (dummy var from region), M orth merica (dummy var from region), MEST Middle East (dummy var from region), CEUROPE Central and Eastern Europe (dummy var from region), SM South merica (dummy var from region), SI sia (dummy variable from region), ICOME98 GDP 998 (UDP) b. Dependent Variable: CORRUPT Corruption 7

8 EXMPLE OF SPSS OUTPUT WITH CLSS SHRED DTBSE Coefficients a Unstandardized Coefficients Standardized Coefficients Model (Constant) ICOME98 GDP 998 (UDP) TOT_POP Population 997, (UDP) SI sia (dummy variable from region) CEUROPE Central and Eastern Europe (dummy var from region) MEST Middle East (dummy var from region) M orth merica (dummy var from region) SM South merica (dummy var from region) SC Scandinavia (dummy var from region) WEURO Western Europe (dummy var from region) a. Dependent Variable: CORRUPT Corruption B Std. Error Beta t Sig. Model FRIC Sub-Saharen frica (dummy variable from region) Excluded Variables b Beta In t Sig. Partial Correlation Collinearity Statistics Tolerance. a a. Predictors in the Model: (Constant), WEURO Western Europe (dummy var from region), TOT_POP Population 997, (UDP), SC Scandinavia (dummy var from region), M orth merica (dummy var from region), MEST Middle East (dummy var from region), CEUROPE Central and Eastern Europe (dummy var from region), SM South merica (dummy var from region), SI sia (dummy variable from region), ICOME98 GDP 998 (UDP) b. Dependent Variable: CORRUPT Corruption 8

9 EXMPLE OF SPSS OUTPUT WITH CLSS SHRED DTBSE 7. Mapping graph MPS /GVR = VR(nation) /GSET = 'World Countries' LYER='Default' /SHOWLBEL = O /TITLE = (Default) MX = 00 /ROVMP=VR(corrupt) SUM=(ME) UMRGES = 4 DISTRIBUTIO = SD LEGEDTITLE = (Default). Maps Corruption Corruption Means.02 to 2.3 (22) to.02 (38) to (40) -.57 to (39) 9

10 EXMPLE OF SPSS OUTPUT WITH CLSS SHRED DTBSE 8. Scatterplot GRPH /SCTTERPLOT(BIVR)=income98 WITH corrupt BY typedemo BY label (IDETIFY) /MISSIG=LISTWISE. Graph 3 2 Z GB Den or Corruption Les SLeo Gam Guy Burk Sene 00 Tanz iger Cuba Fiji Iraq Ven Chil Mex Om Por SKor UE Bah Libya 0000 Ita Jap Type of State on-democratic Semi-democracy ewer democracy Older democracy Population Rsq = GDP 998 (UDP) [You will need to double-click on the graph to edit it for any formatting, such as adding/deleting labels, changing colors/symbols, logging GDP etc.] 0

11 EXMPLE OF SPSS OUTPUT WITH CLSS SHRED DTBSE 9. Interactive 3-D rotating thumb-nail scatterplots IGRPH /VIEWME='Scatterplot' /X = VR(income98) TYPE = SCLE /Y = VR (corrupt) TYPE = SCLE /COLOR = VR(typedemo) TYPE = CTEGORICL /PEL = VR(region) /COORDITE = VERTICL /POITLBEL = VR(label) LL /XLEGTH=3.0 /YLEGTH=3.0 /X2LEGTH=3.0 /CHRTLOOK='OE' /CTORDER VR (label) (SCEDIG VLUES OMITEMPTY) /CTORDER VR(region) (SCEDIG VLUES OMITEMPTY) /CTORDER VR(typedemo) (SCEDIG VLUES OMITEMPTY) /SCTTER COICIDET = OE. Interactive Graph frica sia-pacific C&E Europe Swazi Z Malay Sing Jap Bru Slov Type of State Older democracy ewer democracy Semi-democracy on-democratic Middle East.merica S.merica Isr W Iraq Can US Mex Chil Cuba Scandinavia W.Europe Den Swi

CDAA No. 4 - Part Two - Multiple Regression - Initial Data Screening

CDAA No. 4 - Part Two - Multiple Regression - Initial Data Screening CDAA No. 4 - Part Two - Multiple Regression - Initial Data Screening Variables Entered/Removed b Variables Entered GPA in other high school, test, Math test, GPA, High school math GPA a Variables Removed

More information

TABEL DISTRIBUSI DAN HUBUNGAN LENGKUNG RAHANG DAN INDEKS FASIAL N MIN MAX MEAN SD

TABEL DISTRIBUSI DAN HUBUNGAN LENGKUNG RAHANG DAN INDEKS FASIAL N MIN MAX MEAN SD TABEL DISTRIBUSI DAN HUBUNGAN LENGKUNG RAHANG DAN INDEKS FASIAL Lengkung Indeks fasial rahang Euryprosopic mesoprosopic leptoprosopic Total Sig. n % n % n % n % 0,000 Narrow 0 0 0 0 15 32,6 15 32,6 Normal

More information

I. MODEL. Q3i: Check my . Q29s: I like to see films and TV programs from other countries. Q28e: I like to watch TV shows on a laptop/tablet/phone

I. MODEL. Q3i: Check my  . Q29s: I like to see films and TV programs from other countries. Q28e: I like to watch TV shows on a laptop/tablet/phone 1 Multiple Regression-FORCED-ENTRY HIERARCHICAL MODEL DORIS ACHEME COM 631/731, Spring 2017 Data: Film & TV Usage 2015 I. MODEL IV Block 1: Demographics Sex (female dummy):q30 Age: Q31 Income: Q34 Block

More information

- 1 - Fig. A5.1 Missing value analysis dialog box

- 1 - Fig. A5.1 Missing value analysis dialog box WEB APPENDIX Sarstedt, M. & Mooi, E. (2019). A concise guide to market research. The process, data, and methods using SPSS (3 rd ed.). Heidelberg: Springer. Missing Value Analysis and Multiple Imputation

More information

Descriptives. Graph. [DataSet1] C:\Documents and Settings\BuroK\Desktop\Prestige.sav

Descriptives. Graph. [DataSet1] C:\Documents and Settings\BuroK\Desktop\Prestige.sav GET FILE='C:\Documents and Settings\BuroK\Desktop\Prestige.sav'. DESCRIPTIVES VARIABLES=prestige education income women /STATISTICS=MEAN STDDEV MIN MAX. Descriptives Input Missing Value Handling Resources

More information

1. Crosstabs a. Usia*jenis kelamin

1. Crosstabs a. Usia*jenis kelamin 1. Crosstabs a. Usia*jenis kelamin usia * jenis_kelamin Valid Missing Percent Percent Percent 27 100.0% 0.0% 27 100.0% usia * jenis_kelamin Crosstabulation usia >=30 tahun 31-40 tahun 41-50 tahun

More information

Correlations. Correlations

Correlations. Correlations LAMPIRAN 3 UJI VALIDITAS ketergantun ketergantun ketergantun ketergantun ketergantun gan1 gan2 gan3 gan4 gan5 total1 ketergantungan1 Pearson 1.470(**).179.223.299.614(**) Sig. (2-tailed).009.343.236.109.000

More information

STM103 Spring 2008 INTRODUCTION TO STATA 8.0

STM103 Spring 2008 INTRODUCTION TO STATA 8.0 STM103 Spring 2008 INTRODUCTION TO STATA 8.0 1. PREPARING BEFORE ENTERING THE LAB... 2 Getting the shared dataset... 2 Assignment 1 preparation... 2 2. STARTING A STATA SESSION... 3 Opening, Saving, and

More information

Applied Regression Modeling: A Business Approach

Applied Regression Modeling: A Business Approach i Applied Regression Modeling: A Business Approach Computer software help: SPSS SPSS (originally Statistical Package for the Social Sciences ) is a commercial statistical software package with an easy-to-use

More information

DataSet2. <none> <none> <none>

DataSet2. <none> <none> <none> GGraph Notes Output Created 09-Dec-0 07:50:6 Comments Input Active Dataset Filter Weight Split File DataSet Syntax Resources N of Rows in Working Data File Processor Time Elapsed Time 77 GGRAPH /GRAPHDATASET

More information

Regression. Page 1. Notes. Output Created Comments Data. 26-Mar :31:18. Input. C:\Documents and Settings\BuroK\Desktop\Data Sets\Prestige.

Regression. Page 1. Notes. Output Created Comments Data. 26-Mar :31:18. Input. C:\Documents and Settings\BuroK\Desktop\Data Sets\Prestige. GET FILE='C:\Documents and Settings\BuroK\Desktop\DataSets\Prestige.sav'. GET FILE='E:\MacEwan\Teaching\Stat252\Data\SPSS_data\MENTALID.sav'. DATASET ACTIVATE DataSet1. DATASET CLOSE DataSet2. GET FILE='E:\MacEwan\Teaching\Stat252\Data\SPSS_data\survey_part.sav'.

More information

Independent Variables

Independent Variables 1 Stepwise Multiple Regression Olivia Cohen Com 631, Spring 2017 Data: Film & TV Usage 2015 I. MODEL Independent Variables Demographics Item: Age Item: Income Dummied Item: Gender (Female) Digital Media

More information

LAMPIRAN. Sampel Penelitian

LAMPIRAN. Sampel Penelitian LAMPIRAN Lampiran 1 Daftar Perusahaan Sampel Penelitian No. Kode Kriteria Perusahaan 1 2 3 4 Sampel 1 ADES 1 2 AISA 2 3 ALTO 4 CEKA 5 DAVO 6 DLTA 3 7 ICBP 4 8 INDF 5 9 MLBI 6 10 MYOR 11 PSDN 7 12 ROTI

More information

LAMPIRAN 1 : DATA HASIL PENELITIAN

LAMPIRAN 1 : DATA HASIL PENELITIAN LAMPIRAN 1 : DATA HASIL PENELITIAN SKPD SDM KOMUNIKASI SARANA KOMITMEN MOTIVASI RATA 43 15 74 42 64 78 52,6666667 47 14 66 40 50 80 49,5 55 15 61 40 56 87 52,3333333 49 12 50 41 58 87 49,5 44 12 49 30

More information

An introduction to SPSS

An introduction to SPSS An introduction to SPSS To open the SPSS software using U of Iowa Virtual Desktop... Go to https://virtualdesktop.uiowa.edu and choose SPSS 24. Contents NOTE: Save data files in a drive that is accessible

More information

Regression. Notes. Page 1 25-JAN :21:57. Output Created Comments

Regression. Notes. Page 1 25-JAN :21:57. Output Created Comments /STATISTICS COEFF OUTS CI(95) R ANOVA /CRITERIA=PIN(.05) POUT(.10) /DEPENDENT Favorability /METHOD=ENTER zcontemp ZAnxious6 zallcontact. Regression Notes Output Created Comments Input Missing Value Handling

More information

Applied Regression Modeling: A Business Approach

Applied Regression Modeling: A Business Approach i Applied Regression Modeling: A Business Approach Computer software help: SAS SAS (originally Statistical Analysis Software ) is a commercial statistical software package based on a powerful programming

More information

Correctly Compute Complex Samples Statistics

Correctly Compute Complex Samples Statistics SPSS Complex Samples 15.0 Specifications Correctly Compute Complex Samples Statistics When you conduct sample surveys, use a statistics package dedicated to producing correct estimates for complex sample

More information

Using Large Data Sets Workbook Version A (MEI)

Using Large Data Sets Workbook Version A (MEI) Using Large Data Sets Workbook Version A (MEI) 1 Index Key Skills Page 3 Becoming familiar with the dataset Page 3 Sorting and filtering the dataset Page 4 Producing a table of summary statistics with

More information

ANSWERS -- Prep for Psyc350 Laboratory Final Statistics Part Prep a

ANSWERS -- Prep for Psyc350 Laboratory Final Statistics Part Prep a ANSWERS -- Prep for Psyc350 Laboratory Final Statistics Part Prep a Put the following data into an spss data set: Be sure to include variable and value labels and missing value specifications for all variables

More information

11. Chi Square. Calculate Chi Square for contingency tables. A Chi Square is used to analyze categorical data. It compares observed

11. Chi Square. Calculate Chi Square for contingency tables. A Chi Square is used to analyze categorical data. It compares observed 11. Chi Square Objectives Calculate goodness of fit Chi Square Calculate Chi Square for contingency tables Calculate effect size Save data entry time by weighting cases A Chi Square is used to analyze

More information

Correlations. Butir 1 Pearson Correlation ** Sig. (2-tailed) N

Correlations. Butir 1 Pearson Correlation ** Sig. (2-tailed) N 109 Lampiran olahan Data. 1. Nilai Pelanggan (X1) s Butir 1 Butir 2 Butir 3 Butir Total Butir 1 1.049 -.157.441 ** Sig. (2-tailed).626.120.000 N 100 100 100 100 Butir 2.049 1 -.003.735 ** Sig. (2-tailed).626.978.000

More information

Multiple Regression White paper

Multiple Regression White paper +44 (0) 333 666 7366 Multiple Regression White paper A tool to determine the impact in analysing the effectiveness of advertising spend. Multiple Regression In order to establish if the advertising mechanisms

More information

Copyright 2015 by Sean Connolly

Copyright 2015 by Sean Connolly 1 Copyright 2015 by Sean Connolly All rights reserved. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other

More information

Minitab 17 commands Prepared by Jeffrey S. Simonoff

Minitab 17 commands Prepared by Jeffrey S. Simonoff Minitab 17 commands Prepared by Jeffrey S. Simonoff Data entry and manipulation To enter data by hand, click on the Worksheet window, and enter the values in as you would in any spreadsheet. To then save

More information

Eksamen ERN4110, 6/ VEDLEGG SPSS utskrifter til oppgavene (Av plasshensyn kan utskriftene være noe redigert)

Eksamen ERN4110, 6/ VEDLEGG SPSS utskrifter til oppgavene (Av plasshensyn kan utskriftene være noe redigert) Eksamen ERN4110, 6/9-2018 VEDLEGG SPSS utskrifter til oppgavene (Av plasshensyn kan utskriftene være noe redigert) 1 Oppgave 1 Datafila I SPSS: Variabelnavn Beskrivelse Kjønn Kjønn (1=Kvinne, 2=Mann) Studieinteresse

More information

Crosstabs Notes Output Created 17-Mai :40:54 Comments Input

Crosstabs Notes Output Created 17-Mai :40:54 Comments Input Crosstabs Notes Output Created 17-Mai-2011 01:40:54 Comments Input Data /Users/corinnahornei/Desktop/spss table.sav Active Dataset DatenSet3 Filter Weight Split File N of Rows in Working 189 Data File

More information

An Econometric Study: The Cost of Mobile Broadband

An Econometric Study: The Cost of Mobile Broadband An Econometric Study: The Cost of Mobile Broadband Zhiwei Peng, Yongdon Shin, Adrian Raducanu IATOM13 ENAC January 16, 2014 Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband

More information

CH5: CORR & SIMPLE LINEAR REFRESSION =======================================

CH5: CORR & SIMPLE LINEAR REFRESSION ======================================= STAT 430 SAS Examples SAS5 ===================== ssh xyz@glue.umd.edu, tap sas913 (old sas82), sas https://www.statlab.umd.edu/sasdoc/sashtml/onldoc.htm CH5: CORR & SIMPLE LINEAR REFRESSION =======================================

More information

1. Basic Steps for Data Analysis Data Editor. 2.4.To create a new SPSS file

1. Basic Steps for Data Analysis Data Editor. 2.4.To create a new SPSS file 1 SPSS Guide 2009 Content 1. Basic Steps for Data Analysis. 3 2. Data Editor. 2.4.To create a new SPSS file 3 4 3. Data Analysis/ Frequencies. 5 4. Recoding the variable into classes.. 5 5. Data Analysis/

More information

Example 1 of panel data : Data for 6 airlines (groups) over 15 years (time periods) Example 1

Example 1 of panel data : Data for 6 airlines (groups) over 15 years (time periods) Example 1 Panel data set Consists of n entities or subjects (e.g., firms and states), each of which includes T observations measured at 1 through t time period. total number of observations : nt Panel data have

More information

Conducting a Path Analysis With SPSS/AMOS

Conducting a Path Analysis With SPSS/AMOS Conducting a Path Analysis With SPSS/AMOS Download the PATH-INGRAM.sav data file from my SPSS data page and then bring it into SPSS. The data are those from the research that led to this publication: Ingram,

More information

Brief Guide on Using SPSS 10.0

Brief Guide on Using SPSS 10.0 Brief Guide on Using SPSS 10.0 (Use student data, 22 cases, studentp.dat in Dr. Chang s Data Directory Page) (Page address: http://www.cis.ysu.edu/~chang/stat/) I. Processing File and Data To open a new

More information

Minitab Study Card J ENNIFER L EWIS P RIESTLEY, PH.D.

Minitab Study Card J ENNIFER L EWIS P RIESTLEY, PH.D. Minitab Study Card J ENNIFER L EWIS P RIESTLEY, PH.D. Introduction to Minitab The interface for Minitab is very user-friendly, with a spreadsheet orientation. When you first launch Minitab, you will see

More information

Stat 5100 Handout #19 SAS: Influential Observations and Outliers

Stat 5100 Handout #19 SAS: Influential Observations and Outliers Stat 5100 Handout #19 SAS: Influential Observations and Outliers Example: Data collected on 50 countries relevant to a cross-sectional study of a lifecycle savings hypothesis, which states that the response

More information

IBM SPSS Categories. Predict outcomes and reveal relationships in categorical data. Highlights. With IBM SPSS Categories you can:

IBM SPSS Categories. Predict outcomes and reveal relationships in categorical data. Highlights. With IBM SPSS Categories you can: IBM Software IBM SPSS Statistics 19 IBM SPSS Categories Predict outcomes and reveal relationships in categorical data Highlights With IBM SPSS Categories you can: Visualize and explore complex categorical

More information

Predict Outcomes and Reveal Relationships in Categorical Data

Predict Outcomes and Reveal Relationships in Categorical Data PASW Categories 18 Specifications Predict Outcomes and Reveal Relationships in Categorical Data Unleash the full potential of your data through predictive analysis, statistical learning, perceptual mapping,

More information

Intermediate SPSS. If you have an SPSS dataset (*.sav), you can open it in the following way:

Intermediate SPSS. If you have an SPSS dataset (*.sav), you can open it in the following way: Center for Teaching, Research & Learning Research Support Group at the Social Science Research lab American University, Washington, D.C. http://www.american.edu/provost/ctrl/ 202-885-3862 Intermediate

More information

Excel 2010 with XLSTAT

Excel 2010 with XLSTAT Excel 2010 with XLSTAT J E N N I F E R LE W I S PR I E S T L E Y, PH.D. Introduction to Excel 2010 with XLSTAT The layout for Excel 2010 is slightly different from the layout for Excel 2007. However, with

More information

Introduction. About this Document. What is SPSS. ohow to get SPSS. oopening Data

Introduction. About this Document. What is SPSS. ohow to get SPSS. oopening Data Introduction About this Document This manual was written by members of the Statistical Consulting Program as an introduction to SPSS 12.0. It is designed to assist new users in familiarizing themselves

More information

6:1 LAB RESULTS -WITHIN-S ANOVA

6:1 LAB RESULTS -WITHIN-S ANOVA 6:1 LAB RESULTS -WITHIN-S ANOVA T1/T2/T3/T4. SStotal =(1-12) 2 + + (18-12) 2 = 306.00 = SSpill + SSsubj + SSpxs df = 9-1 = 8 P1 P2 P3 Ms Ms-Mg 1 8 15 8.0-4.0 SSsubj= 3x(-4 2 + ) 4 17 15 12.0 0 = 96.0 13

More information

Chapter 8: Regression. Self-test answers

Chapter 8: Regression. Self-test answers Chapter 8: Regression Self-test answers SELF-TEST Residuals are used to compute which of the three sums of squares? The residuals are used to calculate the residual sum of squares (SSR). This value is

More information

SPSS INSTRUCTION CHAPTER 9

SPSS INSTRUCTION CHAPTER 9 SPSS INSTRUCTION CHAPTER 9 Chapter 9 does no more than introduce the repeated-measures ANOVA, the MANOVA, and the ANCOVA, and discriminant analysis. But, you can likely envision how complicated it can

More information

Cognalysis TM Reserving System User Manual

Cognalysis TM Reserving System User Manual Cognalysis TM Reserving System User Manual Return to Table of Contents 1 Table of Contents 1.0 Starting an Analysis 3 1.1 Opening a Data File....3 1.2 Open an Analysis File.9 1.3 Create Triangles.10 2.0

More information

Research Methods for Business and Management. Session 8a- Analyzing Quantitative Data- using SPSS 16 Andre Samuel

Research Methods for Business and Management. Session 8a- Analyzing Quantitative Data- using SPSS 16 Andre Samuel Research Methods for Business and Management Session 8a- Analyzing Quantitative Data- using SPSS 16 Andre Samuel A Simple Example- Gym Purpose of Questionnaire- to determine the participants involvement

More information

Beta-Regression with SPSS Michael Smithson School of Psychology, The Australian National University

Beta-Regression with SPSS Michael Smithson School of Psychology, The Australian National University 9/1/2005 Beta-Regression with SPSS 1 Beta-Regression with SPSS Michael Smithson School of Psychology, The Australian National University (email: Michael.Smithson@anu.edu.au) SPSS Nonlinear Regression syntax

More information

The following procedures and commands, are covered in this part: Command Purpose Page

The following procedures and commands, are covered in this part: Command Purpose Page Some Procedures in SPSS Part (2) This handout describes some further procedures in SPSS, following on from Part (1). Because some of the procedures covered are complex, with many sub-commands, the descriptions

More information

An Introductory Guide to Stata

An Introductory Guide to Stata An Introductory Guide to Stata Scott L. Minkoff Assistant Professor Department of Political Science Barnard College sminkoff@barnard.edu Updated: July 9, 2012 1 TABLE OF CONTENTS ABOUT THIS GUIDE... 4

More information

SPSS. (Statistical Packages for the Social Sciences)

SPSS. (Statistical Packages for the Social Sciences) Inger Persson SPSS (Statistical Packages for the Social Sciences) SHORT INSTRUCTIONS This presentation contains only relatively short instructions on how to perform basic statistical calculations in SPSS.

More information

IQR = number. summary: largest. = 2. Upper half: Q3 =

IQR = number. summary: largest. = 2. Upper half: Q3 = Step by step box plot Height in centimeters of players on the 003 Women s Worldd Cup soccer team. 157 1611 163 163 164 165 165 165 168 168 168 170 170 170 171 173 173 175 180 180 Determine the 5 number

More information

Correctly Compute Complex Samples Statistics

Correctly Compute Complex Samples Statistics PASW Complex Samples 17.0 Specifications Correctly Compute Complex Samples Statistics When you conduct sample surveys, use a statistics package dedicated to producing correct estimates for complex sample

More information

Factorial ANOVA. Skipping... Page 1 of 18

Factorial ANOVA. Skipping... Page 1 of 18 Factorial ANOVA The potato data: Batches of potatoes randomly assigned to to be stored at either cool or warm temperature, infected with one of three bacterial types. Then wait a set period. The dependent

More information

Bluman & Mayer, Elementary Statistics, A Step by Step Approach, Canadian Edition

Bluman & Mayer, Elementary Statistics, A Step by Step Approach, Canadian Edition Bluman & Mayer, Elementary Statistics, A Step by Step Approach, Canadian Edition Online Learning Centre Technology Step-by-Step - Minitab Minitab is a statistical software application originally created

More information

SPSS QM II. SPSS Manual Quantitative methods II (7.5hp) SHORT INSTRUCTIONS BE CAREFUL

SPSS QM II. SPSS Manual Quantitative methods II (7.5hp) SHORT INSTRUCTIONS BE CAREFUL SPSS QM II SHORT INSTRUCTIONS This presentation contains only relatively short instructions on how to perform some statistical analyses in SPSS. Details around a certain function/analysis method not covered

More information

SAS/STAT 13.1 User s Guide. The SURVEYFREQ Procedure

SAS/STAT 13.1 User s Guide. The SURVEYFREQ Procedure SAS/STAT 13.1 User s Guide The SURVEYFREQ Procedure This document is an individual chapter from SAS/STAT 13.1 User s Guide. The correct bibliographic citation for the complete manual is as follows: SAS

More information

[/TTEST [PERCENT={5}] [{T }] [{DF } [{PROB }] [{COUNTS }] [{MEANS }]] {n} {NOT} {NODF} {NOPROB}] {NOCOUNTS} {NOMEANS}

[/TTEST [PERCENT={5}] [{T }] [{DF } [{PROB }] [{COUNTS }] [{MEANS }]] {n} {NOT} {NODF} {NOPROB}] {NOCOUNTS} {NOMEANS} MVA MVA [VARIABLES=] {varlist} {ALL } [/CATEGORICAL=varlist] [/MAXCAT={25 ** }] {n } [/ID=varname] Description: [/NOUNIVARIATE] [/TTEST [PERCENT={5}] [{T }] [{DF } [{PROB }] [{COUNTS }] [{MEANS }]] {n}

More information

LAMPIRAN B ANALISIS DATA

LAMPIRAN B ANALISIS DATA 100 116 LAMPIRAN B ANALISIS DATA 101 117 Kemandirian Belajar NPAR TESTS /K-S(NORMAL)= /MISSING ANALYSIS. NPar Tests[DataSet0] One-Sample Kolmogorov-Smirnov Test N 91 Normal Parameters a Mean 111.0769 Std.

More information

An Example of Using inter5.exe to Obtain the Graph of an Interaction

An Example of Using inter5.exe to Obtain the Graph of an Interaction An Example of Using inter5.exe to Obtain the Graph of an Interaction This example covers the general use of inter5.exe to produce data from values inserted into a regression equation which can then be

More information

Select those two clusters that result in a minimal increase DeltaWSS(k)

Select those two clusters that result in a minimal increase DeltaWSS(k) Additional Information Chapter 4.1 and 4.3 Ward s method (incremental sum of squares) (pp. 48, 68) step k: Within sum of squares WSS(k) Select those two clusters that result in a minimal increase DeltaWSS(k)

More information

Hypermarket Retail Analysis Customer Buying Behavior. Reachout Analytics Client Sample Report

Hypermarket Retail Analysis Customer Buying Behavior. Reachout Analytics Client Sample Report Hypermarket Retail Analysis Customer Buying Behavior Report Tools Used: R Python WEKA Techniques Applied: Comparesion Tests Association Tests Requirement 1: All the Store Brand significance to Gender Towards

More information

Cell means coding and effect coding

Cell means coding and effect coding Cell means coding and effect coding /* mathregr_3.sas */ %include 'readmath.sas'; title2 ''; /* The data step continues */ if ethnic ne 6; /* Otherwise, throw the case out */ /* Indicator dummy variables

More information

Instructions for Using ABCalc James Alan Fox Northeastern University Updated: August 2009

Instructions for Using ABCalc James Alan Fox Northeastern University Updated: August 2009 Instructions for Using ABCalc James Alan Fox Northeastern University Updated: August 2009 Thank you for using ABCalc, a statistical calculator to accompany several introductory statistics texts published

More information

CREATING SIMULATED DATASETS Edition by G. David Garson and Statistical Associates Publishing Page 1

CREATING SIMULATED DATASETS Edition by G. David Garson and Statistical Associates Publishing Page 1 Copyright @c 2012 by G. David Garson and Statistical Associates Publishing Page 1 @c 2012 by G. David Garson and Statistical Associates Publishing. All rights reserved worldwide in all media. No permission

More information

Laboratory for Two-Way ANOVA: Interactions

Laboratory for Two-Way ANOVA: Interactions Laboratory for Two-Way ANOVA: Interactions For the last lab, we focused on the basics of the Two-Way ANOVA. That is, you learned how to compute a Brown-Forsythe analysis for a Two-Way ANOVA, as well as

More information

THE UNIVERSITY OF BRITISH COLUMBIA FORESTRY 430 and 533. Time: 50 minutes 40 Marks FRST Marks FRST 533 (extra questions)

THE UNIVERSITY OF BRITISH COLUMBIA FORESTRY 430 and 533. Time: 50 minutes 40 Marks FRST Marks FRST 533 (extra questions) THE UNIVERSITY OF BRITISH COLUMBIA FORESTRY 430 and 533 MIDTERM EXAMINATION: October 14, 2005 Instructor: Val LeMay Time: 50 minutes 40 Marks FRST 430 50 Marks FRST 533 (extra questions) This examination

More information

Using SPSS with The Fundamentals of Political Science Research

Using SPSS with The Fundamentals of Political Science Research Using SPSS with The Fundamentals of Political Science Research Paul M. Kellstedt and Guy D. Whitten Department of Political Science Texas A&M University c Paul M. Kellstedt and Guy D. Whitten 2009 Contents

More information

AMELIA II: A Program for Missing Data

AMELIA II: A Program for Missing Data AMELIA II: A Program for Missing Data Amelia II is an R package that performs multiple imputation to deal with missing data, instead of other methods, such as pairwise and listwise deletion. In multiple

More information

Contrasts and Multiple Comparisons

Contrasts and Multiple Comparisons Contrasts and Multiple Comparisons /* onewaymath.sas */ title2 'Oneway with contrasts and multiple comparisons (Exclude Other/DK)'; %include 'readmath.sas'; if ethnic ne 6; /* Otherwise, throw the case

More information

Repeated Measures Part 4: Blood Flow data

Repeated Measures Part 4: Blood Flow data Repeated Measures Part 4: Blood Flow data /* bloodflow.sas */ options linesize=79 pagesize=100 noovp formdlim='_'; title 'Two within-subjecs factors: Blood flow data (NWK p. 1181)'; proc format; value

More information

More information from: https://www.wiseguyreports.com/reports/ dry-cleaning-and-laundry-services-global-marketreport-2018-including

More information from: https://www.wiseguyreports.com/reports/ dry-cleaning-and-laundry-services-global-marketreport-2018-including Report Information More information from: https://www.wiseguyreports.com/reports/2947663-dry-cleaning-and-laundry-services-global-marketreport-2018-including Dry-Cleaning And Laundry Services Global Market

More information

Week 4: Simple Linear Regression III

Week 4: Simple Linear Regression III Week 4: Simple Linear Regression III Marcelo Coca Perraillon University of Colorado Anschutz Medical Campus Health Services Research Methods I HSMP 7607 2017 c 2017 PERRAILLON ARR 1 Outline Goodness of

More information

Indonesia Vietnam. Cambodia 10. China pakistan Philippines Nepal Brunei Japan Singapore India. Thailand 3 Hong Kong 2. Source

Indonesia Vietnam. Cambodia 10. China pakistan Philippines Nepal Brunei Japan Singapore India. Thailand 3 Hong Kong 2. Source 1 9 8 7 6 4 3 2 1 Education Budget as % of GDP Asia & Sth.Pacific Vietnam pakistan Hong Kong 1 9 8 7 6 4 3 2 1 Education Budget as % of GDP Middle East & Nth.Africa U.A.E. Sth.Africa 1 9 8 7 6 4 3 2 1

More information

Complexity Challenges to the Discovery of Relationships in Eddy Current Non-destructive Test Data

Complexity Challenges to the Discovery of Relationships in Eddy Current Non-destructive Test Data Complexity Challenges to the Discovery of Relationships in Eddy Current Non-destructive Test Data CPT John R. Brence United States Military Academy Donald E. Brown, PhD University of Virginia Outline Background

More information

Regression III: Advanced Methods

Regression III: Advanced Methods Lecture 3: Distributions Regression III: Advanced Methods William G. Jacoby Michigan State University Goals of the lecture Examine data in graphical form Graphs for looking at univariate distributions

More information

Using SPSS for Windows for PSY

Using SPSS for Windows for PSY Using SPSS for Windows for PSY222 2008 SPSS is a statistical package (Statistical Package for the Social Sciences) used in a number of Psychology courses at Macquarie, including PSY 222, PSY 331, PSY 418,

More information

Nonparametric Testing

Nonparametric Testing Nonparametric Testing in Excel By Mark Harmon Copyright 2011 Mark Harmon No part of this publication may be reproduced or distributed without the express permission of the author. mark@excelmasterseries.com

More information

Bivariate (Simple) Regression Analysis

Bivariate (Simple) Regression Analysis Revised July 2018 Bivariate (Simple) Regression Analysis This set of notes shows how to use Stata to estimate a simple (two-variable) regression equation. It assumes that you have set Stata up on your

More information

ScholarOne Manuscripts. COGNOS Reports User Guide

ScholarOne Manuscripts. COGNOS Reports User Guide ScholarOne Manuscripts COGNOS Reports User Guide 1-May-2018 Clarivate Analytics ScholarOne Manuscripts COGNOS Reports User Guide Page i TABLE OF CONTENTS USE GET HELP NOW & FAQS... 1 SYSTEM REQUIREMENTS...

More information

DATA DEFINITION PHASE

DATA DEFINITION PHASE Twoway Analysis of Variance Unlike previous problems in the manual, the present problem involves two independent variables (gender of juror and type of crime committed by defendant). There are two levels

More information

STAT - Edit Scroll up the appropriate list to highlight the list name at the very top Press CLEAR, followed by the down arrow or ENTER

STAT - Edit Scroll up the appropriate list to highlight the list name at the very top Press CLEAR, followed by the down arrow or ENTER Entering/Editing Data Use arrows to scroll to the appropriate list and position Enter or edit data, pressing ENTER after each (including the last) Deleting Data (One Value at a Time) Use arrows to scroll

More information

Local Minima in Regression with Optimal Scaling Transformations

Local Minima in Regression with Optimal Scaling Transformations Chapter 2 Local Minima in Regression with Optimal Scaling Transformations CATREG is a program for categorical multiple regression, applying optimal scaling methodology to quantify categorical variables,

More information

ASSOCIATION BETWEEN VARIABLES: SCATTERGRAMS (Like Father, Like Son)

ASSOCIATION BETWEEN VARIABLES: SCATTERGRAMS (Like Father, Like Son) POLI 300 Handouts #11 N. R. Miller ASSOCIATION BETWEEN VARIABLES: SCATTERGRAMS (Like Father, Like Son) Though it is not especially relevant to political science, suppose we want to research the following

More information

SPSS for Survey Analysis

SPSS for Survey Analysis STC: SPSS for Survey Analysis 1 SPSS for Survey Analysis STC: SPSS for Survey Analysis 2 SPSS for Surveys: Contents Background Information... 4 Opening and creating new documents... 5 Starting SPSS...

More information

Generalized least squares (GLS) estimates of the level-2 coefficients,

Generalized least squares (GLS) estimates of the level-2 coefficients, Contents 1 Conceptual and Statistical Background for Two-Level Models...7 1.1 The general two-level model... 7 1.1.1 Level-1 model... 8 1.1.2 Level-2 model... 8 1.2 Parameter estimation... 9 1.3 Empirical

More information

Study Guide. Module 1. Key Terms

Study Guide. Module 1. Key Terms Study Guide Module 1 Key Terms general linear model dummy variable multiple regression model ANOVA model ANCOVA model confounding variable squared multiple correlation adjusted squared multiple correlation

More information

SAS/STAT 14.3 User s Guide The SURVEYFREQ Procedure

SAS/STAT 14.3 User s Guide The SURVEYFREQ Procedure SAS/STAT 14.3 User s Guide The SURVEYFREQ Procedure This document is an individual chapter from SAS/STAT 14.3 User s Guide. The correct bibliographic citation for this manual is as follows: SAS Institute

More information

range: [1,20] units: 1 unique values: 20 missing.: 0/20 percentiles: 10% 25% 50% 75% 90%

range: [1,20] units: 1 unique values: 20 missing.: 0/20 percentiles: 10% 25% 50% 75% 90% ------------------ log: \Term 2\Lecture_2s\regression1a.log log type: text opened on: 22 Feb 2008, 03:29:09. cmdlog using " \Term 2\Lecture_2s\regression1a.do" (cmdlog \Term 2\Lecture_2s\regression1a.do

More information

Learner Expectations UNIT 1: GRAPICAL AND NUMERIC REPRESENTATIONS OF DATA. Sept. Fathom Lab: Distributions and Best Methods of Display

Learner Expectations UNIT 1: GRAPICAL AND NUMERIC REPRESENTATIONS OF DATA. Sept. Fathom Lab: Distributions and Best Methods of Display CURRICULUM MAP TEMPLATE Priority Standards = Approximately 70% Supporting Standards = Approximately 20% Additional Standards = Approximately 10% HONORS PROBABILITY AND STATISTICS Essential Questions &

More information

Conditional and Unconditional Regression with No Measurement Error

Conditional and Unconditional Regression with No Measurement Error Conditional and with No Measurement Error /* reg2ways.sas */ %include 'readsenic.sas'; title2 ''; proc reg; title3 'Conditional Regression'; model infrisk = stay census; proc calis cov; /* Analyze the

More information

Teaching students quantitative methods using resources from the British Birth Cohorts

Teaching students quantitative methods using resources from the British Birth Cohorts Centre for Longitudinal Studies, Institute of Education Teaching students quantitative methods using resources from the British Birth Cohorts Assessment of Cognitive Development through Childhood CognitiveExercises.doc:

More information

Product Catalog. AcaStat. Software

Product Catalog. AcaStat. Software Product Catalog AcaStat Software AcaStat AcaStat is an inexpensive and easy-to-use data analysis tool. Easily create data files or import data from spreadsheets or delimited text files. Run crosstabulations,

More information

Data Analysis and Solver Plugins for KSpread USER S MANUAL. Tomasz Maliszewski

Data Analysis and Solver Plugins for KSpread USER S MANUAL. Tomasz Maliszewski Data Analysis and Solver Plugins for KSpread USER S MANUAL Tomasz Maliszewski tmaliszewski@wp.pl Table of Content CHAPTER 1: INTRODUCTION... 3 1.1. ABOUT DATA ANALYSIS PLUGIN... 3 1.3. ABOUT SOLVER PLUGIN...

More information

2016 SPSS Workshop UBC Research Commons

2016 SPSS Workshop UBC Research Commons " 2016 SPSS Workshop #2 @ UBC Research Commons Part 1: Data Management The Select Cases Command Menu: Data Select Cases 1. Option 1- randomly selecting cases Select Random sample of cases, click on Sample,

More information

Simulating Multivariate Normal Data

Simulating Multivariate Normal Data Simulating Multivariate Normal Data You have a population correlation matrix and wish to simulate a set of data randomly sampled from a population with that structure. I shall present here code and examples

More information

Univariate descriptives

Univariate descriptives Univariate descriptives Johan A. Elkink University College Dublin 18 September 2014 18 September 2014 1 / Outline 1 Graphs for categorical variables 2 Graphs for scale variables 3 Frequency tables 4 Central

More information

Data Mining. ❷Chapter 2 Basic Statistics. Asso.Prof.Dr. Xiao-dong Zhu. Business School, University of Shanghai for Science & Technology

Data Mining. ❷Chapter 2 Basic Statistics. Asso.Prof.Dr. Xiao-dong Zhu. Business School, University of Shanghai for Science & Technology ❷Chapter 2 Basic Statistics Business School, University of Shanghai for Science & Technology 2016-2017 2nd Semester, Spring2017 Contents of chapter 1 1 recording data using computers 2 3 4 5 6 some famous

More information

8. MINITAB COMMANDS WEEK-BY-WEEK

8. MINITAB COMMANDS WEEK-BY-WEEK 8. MINITAB COMMANDS WEEK-BY-WEEK In this section of the Study Guide, we give brief information about the Minitab commands that are needed to apply the statistical methods in each week s study. They are

More information

EDUCATION IN PROC TABULATE I EDUCATION IN PROC TABULATE II

EDUCATION IN PROC TABULATE I EDUCATION IN PROC TABULATE II EDUCTON N PROC TBULTE Georg Morsing - SS nstitute EDUCTON N PROC TBULTE 258 Education in PROC TBULTE ntroduction NECESSRY STTEMENTS CONTENTS PROC TBULTE DT= SSdataset l. ntroduction 2. The TBLE statement

More information

ADMS 3330 FALL 2008 EXAM All Multiple choice Exam (See Answer Key on last page)

ADMS 3330 FALL 2008 EXAM All Multiple choice Exam (See Answer Key on last page) MULTIPLE CHOICE. Choose the letter corresponding to the one alternative that best completes the statement or answers the question. 1. Which of the following are assumptions or requirements of the transportation

More information

Multidimensional Scaling Presentation. Spring Rob Goodman Paul Palisin

Multidimensional Scaling Presentation. Spring Rob Goodman Paul Palisin 1 Multidimensional Scaling Presentation Spring 2009 Rob Goodman Paul Palisin Social Networking Facebook MySpace Instant Messaging Email Youtube Text Messaging Twitter 2 Create a survey for your MDS Enter

More information