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Work inside a single, integrated interface to run descriptive statistics, regression, advanced statistics and many more. Create publication-ready charts, tables and decision trees in one tool.
Integration with open source
Enhance the SPSS syntax with R and Python through specialized extensions. Leverage the 130+ extensions available on IBM Extension Hub, or build your own and share with your peers to create a customized solution.
Easy statistical analysis
Use a simple drag and drop interface to access a wide range of capabilities and work across multiple data sources. Plus, flexible deployment options make purchasing and managing your software easy.
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IBM SPSS Statistics is a comprehensive, easy-to-use set of predictive analytic tools for business users, analysts and statistical programmers. For more than 40 years, organizations of all types have relied on IBM SPSS Statistics to increase revenue, outmaneuver competitors, conduct research and make better decisions. For example, IBM SPSS Statistics has helped organizations to:
* Identify which customers are likely to respond to specific promotional offers * Boost profits and reduce costs by targeting only the most valuable customers * Forecast future trends to better plan organizational strategies, logistics, and manufacturing processes * Detect fraud and minimize business risk * Analyze either/or outcomes, such as patient survival rates or good/bad credit risks * Report results clearly and efficiently * Understand which characteristics consumers relate most closely to their brand * Identify groups, discover relationships between groups, and predict future events
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IBM SPSS Statistics is a product developed by Spss. This site is not directly affiliated with Spss. All trademarks, registered trademarks, product names and company names or logos mentioned herein are the property of their respective owners.
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SPSS Statistics is a software package used for interactive, or batched, statistical analysis. Long produced by SPSS Inc., it was acquired by IBM in 2009. The current versions (2015) are named IBM SPSS Statistics.
The software name originally stood for Statistical Package for the Social Sciences (SPSS),[1] reflecting the original market, although the software is now popular in other fields as well, including the health sciences and marketing.
Overview[edit]
SPSS is a widely used program for statistical analysis in social science. It is also used by market researchers, health researchers, survey companies, government, education researchers, marketing organizations, data miners,[2] and others. The original SPSS manual (Nie, Bent & Hull, 1970)[3] has been described as one of 'sociology's most influential books' for allowing ordinary researchers to do their own statistical analysis.[4] In addition to statistical analysis, data management (case selection, file reshaping, creating derived data) and data documentation (a metadata dictionary is stored in the datafile) are features of the base software.
Statistics included in the base software:
The many features of SPSS Statistics are accessible via pull-down menus or can be programmed with a proprietary 4GLcommand syntax language. Command syntax programming has the benefits of reproducible output, simplifying repetitive tasks, and handling complex data manipulations and analyses. Additionally, some complex applications can only be programmed in syntax and are not accessible through the menu structure. The pull-down menu interface also generates command syntax: this can be displayed in the output, although the default settings have to be changed to make the syntax visible to the user. They can also be pasted into a syntax file using the 'paste' button present in each menu. Programs can be run interactively or unattended, using the supplied Production Job Facility.
Additionally a 'macro' language can be used to write command language subroutines. A Python programmability extension can access the information in the data dictionary and data and dynamically build command syntax programs. The Python programmability extension, introduced in SPSS 14, replaced the less functional SAX Basic 'scripts' for most purposes, although SaxBasic remains available. In addition, the Python extension allows SPSS to run any of the statistics in the free software package R. From version 14 onwards, SPSS can be driven externally by a Python or a VB.NET program using supplied 'plug-ins'. (From Version 20 onwards, these two scripting facilities, as well as many scripts, are included on the installation media and are normally installed by default.)
SPSS Statistics places constraints on internal file structure, data types, data processing, and matching files, which together considerably simplify programming. SPSS datasets have a two-dimensional table structure, where the rows typically represent cases (such as individuals or households) and the columns represent measurements (such as age, sex, or household income). Only two data types are defined: numeric and text (or 'string'). All data processing occurs sequentially case-by-case through the file (dataset). Files can be matched one-to-one and one-to-many, but not many-to-many. In addition to that cases-by-variables structure and processing, there is a separate Matrix session where one can process data as matrices using matrix and linear algebra operations.
The graphical user interface has two views which can be toggled by clicking on one of the two tabs in the bottom left of the SPSS Statistics window. The 'Data View' shows a spreadsheet view of the cases (rows) and variables (columns). Unlike spreadsheets, the data cells can only contain numbers or text, and formulas cannot be stored in these cells. The 'Variable View' displays the metadata dictionary where each row represents a variable and shows the variable name, variable label, value label(s), print width, measurement type, and a variety of other characteristics. Cells in both views can be manually edited, defining the file structure and allowing data entry without using command syntax. This may be sufficient for small datasets. Larger datasets such as statistical surveys are more often created in data entry software, or entered during computer-assisted personal interviewing, by scanning and using optical character recognition and optical mark recognition software, or by direct capture from online questionnaires. These datasets are then read into SPSS.
SPSS Statistics can read and write data from ASCII text files (including hierarchical files), other statistics packages, spreadsheets and databases. SPSS Statistics can read and write to external relational database tables via ODBC and SQL.
Statistical output is to a proprietary file format (*.spv file, supporting pivot tables) for which, in addition to the in-package viewer, a stand-alone reader can be downloaded. The proprietary output can be exported to text or Microsoft Word, PDF, Excel, and other formats. Alternatively, output can be captured as data (using the OMS command), as text, tab-delimited text, PDF, XLS, HTML, XML, SPSS dataset or a variety of graphic image formats (JPEG, PNG, BMP and EMF).
The SPSS logo used prior to the renaming in January 2010.
Several variants of SPSS Statistics exist. SPSS Statistics Gradpacks are highly discounted versions sold only to students. SPSS Statistics Server is a version of SPSS Statistics with a client/server architecture. Add-on packages can enhance the base software with additional features (examples include complex samples which can adjust for clustered and stratified samples, and custom tables which can create publication-ready tables). SPSS Statistics is available under either an annual or a monthly subscription license.
SPSS Statistics launched version 25 on Aug 08, 2017. SPSS v25 adds new and advanced statistics, such as random effects solution results (GENLINMIXED), robust standard errors (GLM/UNIANOVA), and profile plots with error bars within the Advanced Statistics and Custom Tables add-on. V25 also includes new Bayesian Statistics capabilities, a method of statistical inference and publication ready charts, such as powerful new charting capabilities, including new default templates and the ability to share with Microsoft Office applications.[5]
Versions and ownership history[edit]
The software was released in its first version in 1968 as the Statistical Package for the Social Sciences (SPSS) after being developed by Norman H. Nie, Dale H. Bent, and C. Hadlai Hull. Those principals incorporated as SPSS Inc. in 1975. Early versions of SPSS Statistics were written in Fortran and designed for batch processing on mainframes, including for example IBM and ICL versions, originally using punched cards for data and program input. A processing run read a command file of SPSS commands and either a raw input file of fixed format data with a single record type, or a 'getfile' of data saved by a previous run. To save precious computer time an 'edit' run could be done to check command syntax without analysing the data. From version 10 (SPSS-X) in 1983, data files could contain multiple record types.
Prior to SPSS 16.0, different versions of SPSS were available for Windows, Mac OS X and Unix.
SPSS Statistics version 13.0 for Mac OS X was not compatible with Intel-based Macintosh computers, due to the Rosetta emulation software causing errors in calculations. SPSS Statistics 15.0 for Windows needed a downloadable hotfix to be installed in order to be compatible with Windows Vista.
From version 16.0 the same version runs under Windows, Mac, and Linux. The graphical user interface is written in Java. The Mac OS version is provided as a Universal binary, making it fully compatible with both PowerPC and Intel-based Mac hardware.
SPSS Inc announced on July 28, 2009 that it was being acquired by IBM for US$1.2 billion.[6] Because of a dispute about ownership of the name 'SPSS', between 2009 and 2010, the product was referred to as PASW (Predictive Analytics SoftWare).[7] As of January 2010, it became 'SPSS: An IBM Company'. Complete transfer of business to IBM was done by October 1, 2010. By that date, SPSS: An IBM Company ceased to exist. IBM SPSS is now fully integrated into the IBM Corporation, and is one of the brands under IBM Software Group's Business Analytics Portfolio, together with IBM Algorithmics, IBM Cognos and IBM OpenPages.
Companion software in the 'IBM SPSS' family are used for data mining and text analytics (IBM SPSS Modeler), and realtime credit scoring services (IBM SPSS Collaboration and Deployment Services).
SPSS Data Collection and SPSS Dimensions were sold in 2015 to UNICOM Systems, Inc., a division of UNICOM Global, and merged into the integrated software suite UNICOM Intelligence (survey design, survey deployment, data collection, data management and reporting).[8][9][10]
Ibm Spss Version 20 Free DownloadIDA (Interactive Data Analysis)[edit]
IDA (Interactive Data Analysis)[11] was a software package that originated at what formerly was the National Opinion Research Center (NORC), at the University of Chicago. Initially offered on the HP-2000,[12] somewhat later, under the ownership of SPSS, it was also available on DEC's DECSYSTEM-20.[13]
SCSS - Conversational / Columnar SPSS[edit]
SCSS was a software product intended for online use of IBM mainframes.[14]
Although the 'C' was for Conversational, it also represented a distinction regarding how the data was stored: it used a column-oriented rather than a row-oriented (internal) database.[citation needed]
This gave good interactive response time for the SPSS Conversational Statistical System (SCSS), whose strong point, as with SPSS, was Cross-tabulation.[15]
See also[edit]
References[edit]
Further reading[edit]
External links[edit]
Retrieved from 'https://en.wikipedia.org/w/index.php?title=SPSS&oldid=888470477'
Preface vi
SECTION 1
How to use SPSS 1 Ibm Spss Statistics 20 Download
CHAPTER 1
Introduction to SPSS 3 Getting started 3 The SPSS environment 4
CHAPTER 2
Preparation of data files 27 Working example 27 Defining variables 27
CHAPTER 3
Data screening and transformation 37 Working example 37 Errors in data entry 38 Assessing normality 39 Assessing normality by group 44 Variable transformation 44 Data transformation 50
CHAPTER 4
Descriptive statistics 58 Frequency distributions 58 Measures of central tendency and variability 58 Working example 58 The Descriptives command 62
CHAPTER 5
Correlation 64 Assumption testing 64 Working example 65
CHAPTER 6
t-tests 69 Assumption testing 69 Working example 69 The one-sample t-test 70 t-tests with more than one sample 71 Repeated-measures t-test 72 The independent-groups t-test 73
CHAPTER 7
One-way between-groups ANOVA with post-hoc comparisons 79 Assumption testing 79 Working example 80
CHAPTER 8
One-way between-groups ANOVA with planned comparisons 84 Assumption testing 85 Working example 85
CHAPTER 9
Two-way between-groups ANOVA 89 Assumption testing 89 Working example 90
CHAPTER 10
One-way repeated-measures ANOVA 97 Assumption testing 97 Working example 97
CHAPTER 11
Two-way repeated-measures ANOVA 102 Assumption testing 102 Working example 102
CHAPTER 12
Trend analysis 107 Assumption testing 107 Working example 107
CHAPTER 13
Mixed/split plot design (SPANOVA) 111 Assumption testing 111 Working example 111
CHAPTER 14
One-way analysis of covariance (ANCOVA) 117 Assumption testing 117 Working example 118
CHAPTER 15
Reliability analysis 124 Working example 124
CHAPTER 16
Factor analysis 128 Assumption testing 129 Working example 129
CHAPTER 17
Multiple regression 139 Assumption testing 140 Working example 140
CHAPTER 18
Multiple analysis of variance (MANOVA) 151 Assumption testing 151 Working example 152 Data screening 153
CHAPTER 19
Nonparametric techniques 161 Chi-square tests 161 Assumption testing 161 Working example â chi-square test for goodness of fit 162 Working example â chi-square test for relatedness or independence 166 MannâWhitney U test (Wilcoxon rank sum W test) 170 Working example 170 Wilcoxon signed-rank test 172 Working example 172 KruskalâWallis test 175 Working example 175 Friedman test 178 Working example 178 Spearmanâs rank-order correlation 181 Working example 181
CHAPTER 20
Multiple response analysis and multiple dichotomy analysis 184 Multiple response analysis 184 Working example 185 Multiple dichotomy analysis 188 Working example 188
CHAPTER 21
Multidimensional scaling 193 Working example 193
CHAPTER 22
Working with output 201 Editing output in the SPSS Viewer 201 SECTION 2 Analysing data with IBM SPSS 217
CHAPTER 23
Introduction and research questions 219 Working example 219
CHAPTER 24
Practising analytical techniques 251 Section 1: Short homework exercises 251
SECTION 3
Further practice 259
CHAPTER 25
Extra practice 261 Practice example 2: Preparation of data files 262 Practice example 3: Data screening and transformation 263 Practice example 4: Descriptive statistics 263 Practice example 5: Correlation 264 Practice example 6: t-tests 264 Practice example 7: One-way between-groups ANOVA with post-hoc comparisons 264 Practice example 8: One-way between-groups ANOVA with planned comparisons 265 Practice example 9: Two-way between-groups ANOVA 265 Practice example 10: One-way repeatedmeasures ANOVA 265 Practice example 11: Two-way repeatedmeasures ANOVA 265 Practice example 12: Trend analysis 266 Practice example 13: Mixed/split plot design (SPANOVA) 266 Practice example 14: One-way analysis of covariance (ANCOVA) 266 Practice example 15: Reliability analysis 267 Practice example 16: Factor analysis 267 Practice example 17: Regression 267 Practice example 18: MANOVA 268 Practice examples 19aâ19g: Nonparametric tests 268
Appendix 271
Index 277
IBM SPSS Statistics is a comprehensive, easy-to-use set of predictive analytic tools for business users, analysts and statistical programmers. For more than 40 years, organizations of all types have relied on IBM SPSS Statistics to increase revenue, outmaneuver competitors, conduct research and make better decisions. For example, IBM SPSS Statistics has helped organizations to:
* Identify which customers are likely to respond to specific promotional offers * Boost profits and reduce costs by targeting only the most valuable customers * Forecast future trends to better plan organizational strategies, logistics, and manufacturing processes * Detect fraud and minimize business risk * Analyze either/or outcomes, such as patient survival rates or good/bad credit risks * Report results clearly and efficiently * Understand which characteristics consumers relate most closely to their brand * Identify groups, discover relationships between groups, and predict future events
Features
IBM SPSS Statistics is a product developed by Spss. This site is not directly affiliated with Spss. All trademarks, registered trademarks, product names and company names or logos mentioned herein are the property of their respective owners.
All informations about programs or games on this website have been found in open sources on the Internet. All programs and games not hosted on our site. When visitor click 'Download now' button files will downloading directly from official sources(owners sites). QP Download is strongly against the piracy, we do not support any manifestation of piracy. If you think that app/game you own the copyrights is listed on our website and you want to remove it, please contact us. We are DMCA-compliant and gladly to work with you. Please find the DMCA / Removal Request below.
DMCA / REMOVAL REQUEST
Please include the following information in your claim request:
You may send an email to support [at] qpdownload.com for all DMCA / Removal Requests.
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Latest Posts:
How do I uninstall IBM SPSS Statistics in Windows Vista / Windows 7 / Windows 8?
How do I uninstall IBM SPSS Statistics in Windows XP?
How do I uninstall IBM SPSS Statistics in Windows 95, 98, Me, NT, 2000?
Spss Version 20.0
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