LAMPIRAN-LAMPIRAN. Lampiran 1 Nilai ROA, NPF dan FDR Tahun (Triwulan dalam satuan. persen)
|
|
- Wesley Greene
- 7 years ago
- Views:
Transcription
1 LAMPIRAN-LAMPIRAN Lampiran 1 Nilai ROA, NPF dan FDR Tahun (Triwulan dalam satuan persen) Tahun ROA (%) NPF (%) FDR (%) Sumber: Situs Resmi Bank Syariah Mandiri dan Situs Resmi Bank Indonesia ( dan Laporan Keuangan Triwulan PT Bank Syariah Mandiri (data diolah)
2 Lampiran 2 Tabel Frekuensi ROA ROA Frequency Percent Valid Percent Cumulative Percent Valid Total Sumber: Lampiran 1, data diolah
3 Lampiran 3 Tabel Frekuensi NPF NPF Frequency Percent Valid Percent Cumulative Percent Valid Total Sumber: Lampiran 1, data diolah
4 Lampiran 4 Tabel Frekuensi FDR FDR Frequency Percent Valid Percent Cumulative Percent Valid Total Sumber: Lampiran 1, data diolah
5 Lampiran 5. Hasil Uji SPSS 16.0 FREQUENCY ROA Frequency Percent Valid Percent Cumulative Percent Valid Total
6 NPF Frequency Percent Valid Percent Cumulative Percent Valid Total
7 FDR Frequency Percent Valid Percent Cumulative Percent Valid Total
8 Histogram
9
10 NPAR TESTS /K-S(NORMAL)=Y X1 X2 /MISSING ANALYSIS. NPar Tests Notes Output Created 26-Apr :40:03 Comments Input Active Dataset DataSet1 Filter Weight Split File N of Rows in Working Data File 31 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /K-S(NORMAL)=Y X1 X2 /MISSING ANALYSIS. Resources Processor Time 00:00: Elapsed Time 00:00: Number of Cases Allowed a a. Based on availability of workspace memory.
11 [DataSet1] One-Sample Kolmogorov-Smirnov Test ROA NPF FDR N Normal Parameters a Mean Std. Deviation Most Extreme Differences Absolute Positive Negative Kolmogorov-Smirnov Z Asymp. Sig. (2-tailed) a. Test distribution is Normal.
12 REGRESSION /MISSING LISTWISE /STATISTICS COLLIN TOL /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Y /METHOD=ENTER X1 X2. Regression Notes Output Created 26-Apr :28:47 Comments Input Active Dataset DataSet0 Filter Weight Split File N of Rows in Working Data File 31 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics are based on cases with no missing values for any variable used. Syntax REGRESSION /MISSING LISTWISE /STATISTICS COLLIN TOL /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Y /METHOD=ENTER X1 X2. Resources Processor Time 00:00: Elapsed Time 00:00: Memory Required Additional Memory Required for Residual Plots 1628 bytes 0 bytes
13 [DataSet0] Variables Entered/Removed b Variables Variables Model Entered Removed Method 1 FDR, NPF a. Enter a. All requested variables entered. b. Dependent Variable: ROA Coefficients a Collinearity Statistics Model Tolerance VIF 1 NPF FDR a. Dependent Variable: ROA Collinearity Diagnostics a Model Dimensi on Eigenvalue Condition Index Variance Proportions (Constant) NPF FDR a. Dependent Variable: ROA
14 REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Y /METHOD=ENTER X1 X2 /SCATTERPLOT=(*SRESID,*ZPRED). Regression Notes Output Created 26-Apr :44:47 Comments Input Active Dataset DataSet1 Filter Weight Split File N of Rows in Working Data File 31 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics are based on cases with no missing values for any variable used. Syntax REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Y /METHOD=ENTER X1 X2 /SCATTERPLOT=(*SRESID,*ZPRED). Resources Processor Time 00:00: Elapsed Time 00:00: Memory Required Additional Memory Required for Residual Plots 1636 bytes 232 bytes
15 [DataSet1] Variables Entered/Removed b Variables Variables Model Entered Removed Method 1 FDR, NPF a. Enter a. All requested variables entered. b. Dependent Variable: ROA Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate a a. Predictors: (Constant), FDR, NPF b. Dependent Variable: ROA ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total a. Predictors: (Constant), FDR, NPF b. Dependent Variable: ROA
16 Coefficients a Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 (Constant) NPF FDR a. Dependent Variable: ROA Residuals Statistics a Minimum Maximum Mean Std. Deviation N Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual Std. Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: ROA
17 Charts
18 REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Y /METHOD=ENTER X1 X2 /SCATTERPLOT=(*SRESID,*ZPRED). Regression Notes Output Created 26-Apr :44:47 Comments Input Active Dataset DataSet1 Filter Weight Split File N of Rows in Working Data File 31 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics are based on cases with no missing values for any variable used. Syntax REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Y /METHOD=ENTER X1 X2 /SCATTERPLOT=(*SRESID,*ZPRED). Resources Processor Time 00:00: Elapsed Time 00:00: Memory Required Additional Memory Required for Residual Plots 1636 bytes 232 bytes
19 [DataSet1] Variables Entered/Removed b Variables Variables Model Entered Removed Method 1 FDR, NPF a. Enter a. All requested variables entered. b. Dependent Variable: ROA Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate a a. Predictors: (Constant), FDR, NPF b. Dependent Variable: ROA ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total a. Predictors: (Constant), FDR, NPF b. Dependent Variable: ROA
20 Coefficients a Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 (Constant) NPF FDR a. Dependent Variable: ROA Residuals Statistics a Minimum Maximum Mean Std. Deviation N Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual Std. Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: ROA
21 Charts
22 REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Y /METHOD=ENTER X1 X2 /SCATTERPLOT=(*SRESID,*ZPRED). Regression Notes Output Created 26-Apr :47:35 Comments Input Active Dataset DataSet1 Filter Weight Split File N of Rows in Working Data File 31 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics are based on cases with no missing values for any variable used. Syntax REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Y /METHOD=ENTER X1 X2 /SCATTERPLOT=(*SRESID,*ZPRED). Resources Processor Time 00:00: Elapsed Time 00:00: Memory Required 1636 bytes
23 Notes Output Created 26-Apr :47:35 Comments Input Active Dataset DataSet1 Filter Weight Split File N of Rows in Working Data File 31 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics are based on cases with no missing values for any variable used. Syntax REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Y /METHOD=ENTER X1 X2 /SCATTERPLOT=(*SRESID,*ZPRED). Resources Processor Time 00:00: Elapsed Time 00:00: Memory Required Additional Memory Required for Residual Plots 1636 bytes 232 bytes
24 [DataSet1] Variables Entered/Removed b Variables Variables Model Entered Removed Method 1 FDR, NPF a. Enter a. All requested variables entered. b. Dependent Variable: ROA Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate a a. Predictors: (Constant), FDR, NPF b. Dependent Variable: ROA ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total a. Predictors: (Constant), FDR, NPF b. Dependent Variable: ROA
25 Coefficients a Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 (Constant) NPF FDR a. Dependent Variable: ROA Residuals Statistics a Minimum Maximum Mean Std. Deviation N Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual Std. Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: ROA
26 Charts
27
28 DAFTAR RIWAYAT HIDUP Nama saya Maftuhatul Mahmudah, lahir di kota Trenggalek, 8 agustus 1992, saya pernah menempuh pendidikan dasar di SDN III Ngadirenggo mulai tahun 2000 dan lulus pada tahun 2005, kemudian melanjutkan sekolah menengah pertama di MTS Plus Raden Paku tahun 2005 hingga kenaikan kelas 1 ke kelas 2, yaitu tahun 2006, kemudian pindah ke MTS As-Syafi iyah Pogalan mulai kelas 2 pada tahun 2006 sampai lulus jenjang ini tahun 2008, setelah itu menempuh sekolah menengah atas di MAN Trenggalek tahun 2008, dan lulus tahun 2011, kemudian melanjutkan ke IAIN Tulungagung pada tahun Saya pernah melakukan penelitian sebelumnya ketika ada bantuan penelitian dari LP2M yang bersifat penelitian kelompok, dengan judul penelitian Pengaruh Sistem Informasi pada Bank Syariah dalam Menghimpun Nasabah (Studi Kasus pada PT Bank BNI Syariah Kcb. Tulungagung dalam Pembiayaan Murabahah Tahun ).
29
30
31
32
33
34
35
DAFTAR PUSTAKA. Arifin Ali, 2002, Membaca Saham, Edisi I, Yogyakarta : Andi. Bapepam, 2004, Ringkasan Data Perusahaan, Jakarta : Bapepam
03 DAFTAR PUSTAKA Arifin Ali, 00, Membaca Saham, Edisi I, Yogyakarta : Andi Bapepam, 004, Ringkasan Data Perusahaan, Jakarta : Bapepam Darmadji Tjiptono dan Fakhruddin M Hendy, 006, Pasar Modal di Indonesia,
More informationMultiple Regression in SPSS This example shows you how to perform multiple regression. The basic command is regression : linear.
Multiple Regression in SPSS This example shows you how to perform multiple regression. The basic command is regression : linear. In the main dialog box, input the dependent variable and several predictors.
More informationSimple Linear Regression, Scatterplots, and Bivariate Correlation
1 Simple Linear Regression, Scatterplots, and Bivariate Correlation This section covers procedures for testing the association between two continuous variables using the SPSS Regression and Correlate analyses.
More informationModeration. Moderation
Stats - Moderation Moderation A moderator is a variable that specifies conditions under which a given predictor is related to an outcome. The moderator explains when a DV and IV are related. Moderation
More informationSPSS Guide: Regression Analysis
SPSS Guide: Regression Analysis I put this together to give you a step-by-step guide for replicating what we did in the computer lab. It should help you run the tests we covered. The best way to get familiar
More informationChapter Seven. Multiple regression An introduction to multiple regression Performing a multiple regression on SPSS
Chapter Seven Multiple regression An introduction to multiple regression Performing a multiple regression on SPSS Section : An introduction to multiple regression WHAT IS MULTIPLE REGRESSION? Multiple
More informationMultiple Regression. Page 24
Multiple Regression Multiple regression is an extension of simple (bi-variate) regression. The goal of multiple regression is to enable a researcher to assess the relationship between a dependent (predicted)
More informationDoing Multiple Regression with SPSS. In this case, we are interested in the Analyze options so we choose that menu. If gives us a number of choices:
Doing Multiple Regression with SPSS Multiple Regression for Data Already in Data Editor Next we want to specify a multiple regression analysis for these data. The menu bar for SPSS offers several options:
More information1.1. Simple Regression in Excel (Excel 2010).
.. Simple Regression in Excel (Excel 200). To get the Data Analysis tool, first click on File > Options > Add-Ins > Go > Select Data Analysis Toolpack & Toolpack VBA. Data Analysis is now available under
More informationChapter 13 Introduction to Linear Regression and Correlation Analysis
Chapter 3 Student Lecture Notes 3- Chapter 3 Introduction to Linear Regression and Correlation Analsis Fall 2006 Fundamentals of Business Statistics Chapter Goals To understand the methods for displaing
More informationJD Eveland PhD. Presented to TUI University Faculty Research Forum. 30 November 2007
JD Eveland PhD Presented to TUI University Faculty Research Forum 30 November 2007 A follow-up to the CARMA presentation by Dr. James LeBreton on Relative Importance of Predictors with Regression Models
More informationSPSS-Applications (Data Analysis)
CORTEX fellows training course, University of Zurich, October 2006 Slide 1 SPSS-Applications (Data Analysis) Dr. Jürg Schwarz, juerg.schwarz@schwarzpartners.ch Program 19. October 2006: Morning Lessons
More informationSimple linear regression
Simple linear regression Introduction Simple linear regression is a statistical method for obtaining a formula to predict values of one variable from another where there is a causal relationship between
More informationThe Not-Even-Remotely Close to Being a Complete Guide to SPSS / PASW Syntax. (For SPSS / PASW v.18+)
The Not-Even-Remotely Close to Being a Complete Guide to SPSS / PASW Syntax (For SPSS / PASW v.18+) Dr. Bryan R. Burnham Department of Psychology University of Scranton 1 of 49 Table of Contents 1. What
More informationStudent debt from higher education attendance is an increasingly troubling problem in the
Morrie Swerlick Student Debt Policy Memo 2/23/2012 Student debt from higher education attendance is an increasingly troubling problem in the United States. Due to rising costs and shrinking state expenditures,
More informationUsing Correlation and Regression: Mediation, Moderation, and More
Using Correlation and Regression: Mediation, Moderation, and More Part 2: Mediation analysis with regression Claremont Graduate University Professional Development Workshop August 22, 2015 Dale Berger,
More informationNCSS Statistical Software Principal Components Regression. In ordinary least squares, the regression coefficients are estimated using the formula ( )
Chapter 340 Principal Components Regression Introduction is a technique for analyzing multiple regression data that suffer from multicollinearity. When multicollinearity occurs, least squares estimates
More informationChapter 23. Inferences for Regression
Chapter 23. Inferences for Regression Topics covered in this chapter: Simple Linear Regression Simple Linear Regression Example 23.1: Crying and IQ The Problem: Infants who cry easily may be more easily
More informationModerator and Mediator Analysis
Moderator and Mediator Analysis Seminar General Statistics Marijtje van Duijn October 8, Overview What is moderation and mediation? What is their relation to statistical concepts? Example(s) October 8,
More informationFactor Analysis. Principal components factor analysis. Use of extracted factors in multivariate dependency models
Factor Analysis Principal components factor analysis Use of extracted factors in multivariate dependency models 2 KEY CONCEPTS ***** Factor Analysis Interdependency technique Assumptions of factor analysis
More informationSPSS TUTORIAL & EXERCISE BOOK
UNIVERSITY OF MISKOLC Faculty of Economics Institute of Business Information and Methods Department of Business Statistics and Economic Forecasting PETRA PETROVICS SPSS TUTORIAL & EXERCISE BOOK FOR BUSINESS
More informationMulticollinearity Richard Williams, University of Notre Dame, http://www3.nd.edu/~rwilliam/ Last revised January 13, 2015
Multicollinearity Richard Williams, University of Notre Dame, http://www3.nd.edu/~rwilliam/ Last revised January 13, 2015 Stata Example (See appendices for full example).. use http://www.nd.edu/~rwilliam/stats2/statafiles/multicoll.dta,
More informationANALYSIS OF FACTORS THAT INFLUENCE THE ATTITUDE OF ENTREPRENEURS IN CHOOSING FINANCING SHARIA BANK
ANALYSIS OF FACTORS THAT INFLUENCE THE ATTITUDE OF ENTREPRENEURS IN CHOOSING FINANCING SHARIA BANK Ery Wibowo Faculty of Economics, University of Muhammadiyah Semarang Indonesia E-mail : erywibowo_08@yahoo.co.id
More informationEPS 625 INTERMEDIATE STATISTICS FRIEDMAN TEST
EPS 625 INTERMEDIATE STATISTICS The Friedman test is an extension of the Wilcoxon test. The Wilcoxon test can be applied to repeated-measures data if participants are assessed on two occasions or conditions
More informationCreating a Campus Netflow Model
Creating a Campus Netflow Model HUNG-JEN YANG, MIAO-KUEI HO, LUNG-HSING KUO Department of industry technology Education National Kaohsiung Normal University No.116, Heping 1st Rd., Lingya District, Kaohsiung
More informationUnivariate Regression
Univariate Regression Correlation and Regression The regression line summarizes the linear relationship between 2 variables Correlation coefficient, r, measures strength of relationship: the closer r is
More informationSPSS Guide How-to, Tips, Tricks & Statistical Techniques
SPSS Guide How-to, Tips, Tricks & Statistical Techniques Support for the course Research Methodology for IB Also useful for your BSc or MSc thesis March 2014 Dr. Marijke Leliveld Jacob Wiebenga, MSc CONTENT
More informationC:\Users\<your_user_name>\AppData\Roaming\IEA\IDBAnalyzerV3
Installing the IDB Analyzer (Version 3.1) Installing the IDB Analyzer (Version 3.1) A current version of the IDB Analyzer is available free of charge from the IEA website (http://www.iea.nl/data.html,
More informationChapter 2 Probability Topics SPSS T tests
Chapter 2 Probability Topics SPSS T tests Data file used: gss.sav In the lecture about chapter 2, only the One-Sample T test has been explained. In this handout, we also give the SPSS methods to perform
More informationData Analysis for Marketing Research - Using SPSS
North South University, School of Business MKT 63 Marketing Research Instructor: Mahmood Hussain, PhD Data Analysis for Marketing Research - Using SPSS Introduction In this part of the class, we will learn
More informationFalse. Model 2 is not a special case of Model 1, because Model 2 includes X5, which is not part of Model 1. What she ought to do is estimate
Sociology 59 - Research Statistics I Final Exam Answer Key December 6, 00 Where appropriate, show your work - partial credit may be given. (On the other hand, don't waste a lot of time on excess verbiage.)
More informationProjects Involving Statistics (& SPSS)
Projects Involving Statistics (& SPSS) Academic Skills Advice Starting a project which involves using statistics can feel confusing as there seems to be many different things you can do (charts, graphs,
More informationAdditional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jin-tselink/tselink.htm
Mgt 540 Research Methods Data Analysis 1 Additional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jin-tselink/tselink.htm http://web.utk.edu/~dap/random/order/start.htm
More informationCorrelation and Regression Analysis: SPSS
Correlation and Regression Analysis: SPSS Bivariate Analysis: Cyberloafing Predicted from Personality and Age These days many employees, during work hours, spend time on the Internet doing personal things,
More informationDEPARTMENT OF PSYCHOLOGY UNIVERSITY OF LANCASTER MSC IN PSYCHOLOGICAL RESEARCH METHODS ANALYSING AND INTERPRETING DATA 2 PART 1 WEEK 9
DEPARTMENT OF PSYCHOLOGY UNIVERSITY OF LANCASTER MSC IN PSYCHOLOGICAL RESEARCH METHODS ANALYSING AND INTERPRETING DATA 2 PART 1 WEEK 9 Analysis of covariance and multiple regression So far in this course,
More informationComparing a Multiple Regression Model Across Groups
Comparing a Multiple Regression Across Groups We might want to know whether a particular set of predictors leads to a multiple regression model that works equally effectively for two (or more) different
More informationPredictor Coef StDev T P Constant 970667056 616256122 1.58 0.154 X 0.00293 0.06163 0.05 0.963. S = 0.5597 R-Sq = 0.0% R-Sq(adj) = 0.
Statistical analysis using Microsoft Excel Microsoft Excel spreadsheets have become somewhat of a standard for data storage, at least for smaller data sets. This, along with the program often being packaged
More informationMultiple Regression Using SPSS
Multiple Regression Using SPSS The following sections have been adapted from Field (2009) Chapter 7. These sections have been edited down considerably and I suggest (especially if you re confused) that
More informationTHE INFLUENCES OF PRODUCTIVE ZAKAH MENTORING TO THE SAVING BEHAVIOR AND THE PROSPERITY OF POOR HOUSEWIFE
Rizky Andriati & Nurul Huda: The Influences of Productive Zakah 207 THE INFLUENCES OF PRODUCTIVE ZAKAH MENTORING TO THE SAVING BEHAVIOR AND THE PROSPERITY OF POOR HOUSEWIFE Rizky Andriati & Nurul Huda
More informationKSTAT MINI-MANUAL. Decision Sciences 434 Kellogg Graduate School of Management
KSTAT MINI-MANUAL Decision Sciences 434 Kellogg Graduate School of Management Kstat is a set of macros added to Excel and it will enable you to do the statistics required for this course very easily. To
More informationA Basic Guide to Analyzing Individual Scores Data with SPSS
A Basic Guide to Analyzing Individual Scores Data with SPSS Step 1. Clean the data file Open the Excel file with your data. You may get the following message: If you get this message, click yes. Delete
More informationDirections for using SPSS
Directions for using SPSS Table of Contents Connecting and Working with Files 1. Accessing SPSS... 2 2. Transferring Files to N:\drive or your computer... 3 3. Importing Data from Another File Format...
More informationThe Dummy s Guide to Data Analysis Using SPSS
The Dummy s Guide to Data Analysis Using SPSS Mathematics 57 Scripps College Amy Gamble April, 2001 Amy Gamble 4/30/01 All Rights Rerserved TABLE OF CONTENTS PAGE Helpful Hints for All Tests...1 Tests
More informationEvaluation Human Resourches Information System (HRIS) The University Of Bina Darma Using End User Computing Satisfaction (EUCS)
The 4th ICIBA 2015, International Conference on Information Technology and Engineering Application Palembang-Indonesia, 20-21 February 2015 Evaluation Human Resourches Information System (HRIS) The University
More informationOutliers Richard Williams, University of Notre Dame, http://www3.nd.edu/~rwilliam/ Last revised April 7, 2016
Outliers Richard Williams, University of Notre Dame, http://www3.nd.edu/~rwilliam/ Last revised April 7, 2016 These notes draw heavily from several sources, including Fox s Regression Diagnostics; Pindyck
More informationTHE PERFORMANCE OF THE BACHELOR EDUCATION IN-SERVICE TEACHERS PROGRAMME (ICT-BASED BEITP) BACHELOR GRADUATED AND ITS DETERMINANT.
THE PERFORMANCE OF THE BACHELOR EDUCATION IN-SERVICE TEACHERS PROGRAMME (ICT-BASED BEITP) BACHELOR GRADUATED AND ITS DETERMINANT Slameto Primary Teacher Educational Program, Satya Wacana Christian University,
More informationDidacticiel - Études de cas
1 Topic Regression analysis with LazStats (OpenStat). LazStat 1 is a statistical software which is developed by Bill Miller, the father of OpenStat, a wellknow tool by statisticians since many years. These
More informationData driven approach in analyzing energy consumption data in buildings. Office of Environmental Sustainability Ian Tan
Data driven approach in analyzing energy consumption data in buildings Office of Environmental Sustainability Ian Tan Background Real time energy consumption data of buildings in terms of electricity (kwh)
More informationThis chapter will demonstrate how to perform multiple linear regression with IBM SPSS
CHAPTER 7B Multiple Regression: Statistical Methods Using IBM SPSS This chapter will demonstrate how to perform multiple linear regression with IBM SPSS first using the standard method and then using the
More informationwww.kellogg.northwestern.edu/kis/tek/ongoing/spss.htm
First version: October 11, 2004 Last revision: January 14, 2005 KELLOGG RESEARCH COMPUTING Introduction to SPSS SPSS is a statistical package commonly used in the social sciences, particularly in marketing,
More informationIntroduction. Research Problem. Larojan Chandrasegaran (1), Janaki Samuel Thevaruban (2)
Larojan Chandrasegaran (1), Janaki Samuel Thevaruban (2) Determining Factors on Applicability of the Computerized Accounting System in Financial Institutions in Sri Lanka (1) Department of Finance and
More informationSPSS Resources. 1. See website (readings) for SPSS tutorial & Stats handout
Analyzing Data SPSS Resources 1. See website (readings) for SPSS tutorial & Stats handout Don t have your own copy of SPSS? 1. Use the libraries to analyze your data 2. Download a trial version of SPSS
More informationDeterminants of the Total Quality Management Implementation in SMEs in Iran (Case of Metal Industry)
International Journal of Business and Social Science Vol. 4 No. 16; December 2013 Determinants of the Total Quality Management Implementation in SMEs in Iran (Case of Metal Industry) Hamed Ramezani Planning
More informationPRODUCTIVITY IMPROVEMENT VIA SIMULATION METHOD (MANUFACTURING INDUSTRY) HASBULLAH BIN MAT ISA
PRODUCTIVITY IMPROVEMENT VIA SIMULATION METHOD (MANUFACTURING INDUSTRY) HASBULLAH BIN MAT ISA Thesis submitted in fulfillment of the requirements for the award of the degree of Bachelor of Mechanical Engineering
More information1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number
1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number A. 3(x - x) B. x 3 x C. 3x - x D. x - 3x 2) Write the following as an algebraic expression
More informationJanuary 26, 2009 The Faculty Center for Teaching and Learning
THE BASICS OF DATA MANAGEMENT AND ANALYSIS A USER GUIDE January 26, 2009 The Faculty Center for Teaching and Learning THE BASICS OF DATA MANAGEMENT AND ANALYSIS Table of Contents Table of Contents... i
More informationMISSING DATA TECHNIQUES WITH SAS. IDRE Statistical Consulting Group
MISSING DATA TECHNIQUES WITH SAS IDRE Statistical Consulting Group ROAD MAP FOR TODAY To discuss: 1. Commonly used techniques for handling missing data, focusing on multiple imputation 2. Issues that could
More informationRegression Analysis (Spring, 2000)
Regression Analysis (Spring, 2000) By Wonjae Purposes: a. Explaining the relationship between Y and X variables with a model (Explain a variable Y in terms of Xs) b. Estimating and testing the intensity
More informationHYPOTHESIS TESTING WITH SPSS:
HYPOTHESIS TESTING WITH SPSS: A NON-STATISTICIAN S GUIDE & TUTORIAL by Dr. Jim Mirabella SPSS 14.0 screenshots reprinted with permission from SPSS Inc. Published June 2006 Copyright Dr. Jim Mirabella CHAPTER
More informationOnline versus Traditional Learning: A Comparison Study of Colorado Community College Science Classes
Online versus Traditional Learning: A Comparison Study of Colorado Community College Science Classes Introduction Students are currently given more and more options in postsecondary education be it the
More informationHYPOTHESIS TESTING: CONFIDENCE INTERVALS, T-TESTS, ANOVAS, AND REGRESSION
HYPOTHESIS TESTING: CONFIDENCE INTERVALS, T-TESTS, ANOVAS, AND REGRESSION HOD 2990 10 November 2010 Lecture Background This is a lightning speed summary of introductory statistical methods for senior undergraduate
More informationCan academic mentoring reduce the time to get a degree?
Can academic mentoring reduce the time to get a degree? Claudia Marin SFPC University of Bari claudia.marin@uniba.it ----------------- Anna Rinaldi DEM University of Bari amc.rinaldi@gmail.com We run a
More informationOne-Way ANOVA using SPSS 11.0. SPSS ANOVA procedures found in the Compare Means analyses. Specifically, we demonstrate
1 One-Way ANOVA using SPSS 11.0 This section covers steps for testing the difference between three or more group means using the SPSS ANOVA procedures found in the Compare Means analyses. Specifically,
More informationThe Impact of Affective Human Resources Management Practices on the Financial Performance of the Saudi Banks
327 The Impact of Affective Human Resources Management Practices on the Financial Performance of the Saudi Banks Abdullah Attia AL-Zahrani King Saud University azahrani@ksu.edu.sa Ahmad Aref Almazari*
More informationData analysis process
Data analysis process Data collection and preparation Collect data Prepare codebook Set up structure of data Enter data Screen data for errors Exploration of data Descriptive Statistics Graphs Analysis
More informationData Analysis Tools. Tools for Summarizing Data
Data Analysis Tools This section of the notes is meant to introduce you to many of the tools that are provided by Excel under the Tools/Data Analysis menu item. If your computer does not have that tool
More information1. What is the critical value for this 95% confidence interval? CV = z.025 = invnorm(0.025) = 1.96
1 Final Review 2 Review 2.1 CI 1-propZint Scenario 1 A TV manufacturer claims in its warranty brochure that in the past not more than 10 percent of its TV sets needed any repair during the first two years
More information5. Linear Regression
5. Linear Regression Outline.................................................................... 2 Simple linear regression 3 Linear model............................................................. 4
More informationData Mining for Model Creation. Presentation by Paul Below, EDS 2500 NE Plunkett Lane Poulsbo, WA USA 98370 paul.below@eds.
Sept 03-23-05 22 2005 Data Mining for Model Creation Presentation by Paul Below, EDS 2500 NE Plunkett Lane Poulsbo, WA USA 98370 paul.below@eds.com page 1 Agenda Data Mining and Estimating Model Creation
More informationAPPLICATION OF LINEAR REGRESSION MODEL FOR POISSON DISTRIBUTION IN FORECASTING
APPLICATION OF LINEAR REGRESSION MODEL FOR POISSON DISTRIBUTION IN FORECASTING Sulaimon Mutiu O. Department of Statistics & Mathematics Moshood Abiola Polytechnic, Abeokuta, Ogun State, Nigeria. Abstract
More informationTHE RELATIONSHIP BETWEEN WORKING CAPITAL MANAGEMENT AND DIVIDEND PAYOUT RATIO OF FIRMS LISTED IN NAIROBI SECURITIES EXCHANGE
International Journal of Economics, Commerce and Management United Kingdom Vol. III, Issue 11, November 2015 http://ijecm.co.uk/ ISSN 2348 0386 THE RELATIONSHIP BETWEEN WORKING CAPITAL MANAGEMENT AND DIVIDEND
More informationOrdinal Regression. Chapter
Ordinal Regression Chapter 4 Many variables of interest are ordinal. That is, you can rank the values, but the real distance between categories is unknown. Diseases are graded on scales from least severe
More informationSPSS Notes (SPSS version 15.0)
SPSS Notes (SPSS version 15.0) Annie Herbert Salford Royal Hospitals NHS Trust July 2008 Contents Page Getting Started 1 1 Opening SPSS 1 2 Layout of SPSS 2 2.1 Windows 2 2.2 Saving Files 3 3 Creating
More informationA SUCCESFULL WAY TO SELL HANDICRAFTS IN ALBANIA
International Journal of Economics, Commerce and Management United Kingdom Vol. III, Issue 4, April 2015 http://ijecm.co.uk/ ISSN 2348 0386 A SUCCESFULL WAY TO SELL HANDICRAFTS IN ALBANIA EMPIRICAL EXPLORATION
More informationPROFITABILITY ANALYSIS
PROFITABILITY ANALYSIS Ekonomi Teknik Kimia By Dr. Istadi 2007 Schedule Time Value of Money (Interest Rate) & Cash Flow Depreciation & Salvage Value Profitability Analysis Selection of Alternatif Investment
More informationA Brief Introduction to SPSS Factor Analysis
A Brief Introduction to SPSS Factor Analysis SPSS has a procedure that conducts exploratory factor analysis. Before launching into a step by step example of how to use this procedure, it is recommended
More informationDoes organizational culture cheer organizational profitability? A case study on a Bangalore based Software Company
Does organizational culture cheer organizational profitability? A case study on a Bangalore based Software Company S Deepalakshmi Assistant Professor Department of Commerce School of Business, Alliance
More informationIndependent t- Test (Comparing Two Means)
Independent t- Test (Comparing Two Means) The objectives of this lesson are to learn: the definition/purpose of independent t-test when to use the independent t-test the use of SPSS to complete an independent
More informationData analysis and regression in Stata
Data analysis and regression in Stata This handout shows how the weekly beer sales series might be analyzed with Stata (the software package now used for teaching stats at Kellogg), for purposes of comparing
More informationAdvertising value of mobile marketing through acceptance among youth in Karachi
MPRA Munich Personal RePEc Archive Advertising value of mobile marketing through acceptance among youth in Karachi Suleman Syed Akbar and Rehan Azam and Danish Muhammad IQRA UNIVERSITY 1. September 2012
More informationEFFECT OF VOLUNTARY DISCLOSURE AND SHARE LIQUIDITY OF THE CAPITAL MARKET IN INDONESIAN STOCK EXCHANGE
EFFECT OF VOLUNTARY DISCLOSURE AND SHARE LIQUIDITY OF THE CAPITAL MARKET IN INDONESIAN STOCK EXCHANGE Erlynda Y. Kasim Doctoral Student at Padjajaran University, Bandung, Indonesia Lecturer at STIE Ekuitas,
More informationCase Study 1: Activity Analysis of Control for Micro Lending
362 Business Intelligence Journal July THREE CASE STUDIES ON BANK NAGARI PADANG (INDONESIA) HEADQUARTERS AND MAIN BRANCH Heryanto, (PhD) Chief of RfD of the Chamber of Commerce and Industry; Professor
More informationData Analysis. Using Excel. Jeffrey L. Rummel. BBA Seminar. Data in Excel. Excel Calculations of Descriptive Statistics. Single Variable Graphs
Using Excel Jeffrey L. Rummel Emory University Goizueta Business School BBA Seminar Jeffrey L. Rummel BBA Seminar 1 / 54 Excel Calculations of Descriptive Statistics Single Variable Graphs Relationships
More informationHow To Find Out What Is The Recipe For A Bank Loan
BANK S LENDING DECISION TO THE INDUSTRIAL SECTORS Ms.Sangeeta Mohanty Assistant Professor, Academy of Business Administration, Industrial Estate (S1/25) Angaragadia, Balasore, Orissa (756001) Abstract
More informationLogistic Regression (a type of Generalized Linear Model)
Logistic Regression (a type of Generalized Linear Model) 1/36 Today Review of GLMs Logistic Regression 2/36 How do we find patterns in data? We begin with a model of how the world works We use our knowledge
More informationKey Words: financial ratio.; Earnings per share; Amman Stock Market JEL Classification: G
THE EFFECT OF FINANCIAL RATIOS, FIRM SIZE AND CASH FLOWS FROM OPERATING ACTIVITIES ON EARNINGS PER SHARE: (AN APPLIED STUDY: ON JORDANIAN INDUSTRIAL SECTOR) Khalaf Taani Irbid National University, Irbid-Jordan
More informationFinal Exam Practice Problem Answers
Final Exam Practice Problem Answers The following data set consists of data gathered from 77 popular breakfast cereals. The variables in the data set are as follows: Brand: The brand name of the cereal
More informationData Mining and Data Warehousing. Henryk Maciejewski. Data Mining Predictive modelling: regression
Data Mining and Data Warehousing Henryk Maciejewski Data Mining Predictive modelling: regression Algorithms for Predictive Modelling Contents Regression Classification Auxiliary topics: Estimation of prediction
More informationRegression Analysis: A Complete Example
Regression Analysis: A Complete Example This section works out an example that includes all the topics we have discussed so far in this chapter. A complete example of regression analysis. PhotoDisc, Inc./Getty
More informationICBASS-188 Effect of Debt Contracts Negotiation Toward Company To Perform Revaluation of Fixed Assets and Its Implications Toward Income Tax Expense
ICBASS-188 Effect of Debt Contracts Negotiation Toward Company To Perform Revaluation of Fixed Assets and Its Implications Toward Income Tax Expense Erly Sherlita erly.sherlita@widyatama.ac.id Diana Sari
More informationUsing R for Linear Regression
Using R for Linear Regression In the following handout words and symbols in bold are R functions and words and symbols in italics are entries supplied by the user; underlined words and symbols are optional
More informationMultiple Linear Regression
Multiple Linear Regression A regression with two or more explanatory variables is called a multiple regression. Rather than modeling the mean response as a straight line, as in simple regression, it is
More informationANALYSIS OF USER ACCEPTANCE OF A NETWORK MONITORING SYSTEM WITH A FOCUS ON ICT TEACHERS
ANALYSIS OF USER ACCEPTANCE OF A NETWORK MONITORING SYSTEM WITH A FOCUS ON ICT TEACHERS Siti Rahayu Abdul Aziz 1, Mohamad Ibrahim 2, and Suhaimi Sauti 3 1 Universiti Teknologi MARA, Malaysia, rahayu@fskm.uitm.edu.my
More informationOutline. Topic 4 - Analysis of Variance Approach to Regression. Partitioning Sums of Squares. Total Sum of Squares. Partitioning sums of squares
Topic 4 - Analysis of Variance Approach to Regression Outline Partitioning sums of squares Degrees of freedom Expected mean squares General linear test - Fall 2013 R 2 and the coefficient of correlation
More informationTrust, Job Satisfaction, Organizational Commitment, and the Volunteer s Psychological Contract
Trust, Job Satisfaction, Commitment, and the Volunteer s Psychological Contract Becky J. Starnes, Ph.D. Austin Peay State University Clarksville, Tennessee, USA starnesb@apsu.edu Abstract Studies indicate
More informationChapter 7: Simple linear regression Learning Objectives
Chapter 7: Simple linear regression Learning Objectives Reading: Section 7.1 of OpenIntro Statistics Video: Correlation vs. causation, YouTube (2:19) Video: Intro to Linear Regression, YouTube (5:18) -
More informationPage 1 of 1. Page 2 of 2 % &! " '! ( ' ( $) * +, - % -. !" # $
Argosoft Pos Server Panduan Page 1 of 1 Isi Mulai... 3 Menguasai... 5 Pilihan... 7 Menentukan catatan... 10 Menentukan Linkungan... 11 Linkungan betul... 12 Menentukan linkungan berganda... 13 Menambahkan
More information6 Variables: PD MF MA K IAH SBS
options pageno=min nodate formdlim='-'; title 'Canonical Correlation, Journal of Interpersonal Violence, 10: 354-366.'; data SunitaPatel; infile 'C:\Users\Vati\Documents\StatData\Sunita.dat'; input Group
More informationPsych. Research 1 Guide to SPSS 11.0
SPSS GUIDE 1 Psych. Research 1 Guide to SPSS 11.0 I. What is SPSS: SPSS (Statistical Package for the Social Sciences) is a data management and analysis program. It allows us to store and analyze very large
More information