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Sidhiqul Akbar 
ROLL NO 39
Contents 
 Statistical package introduction 
 Statistical Packages 
 Introduction to SPSS 
 Features of SPSS 
 SPSS 
 EXCEL
Statistical package introduction 
 It is a relatively easy package to learn. 
 Stata has an easy spreadsheet-style data 
representation 
 - Stata keeps good records of your actions. 
 - It is relatively cheap (both in cost and memory) 
 Stata license is perpetual – if you buy it, you own it 
forever.
Statistical packages 
 There are many statistical packages (Stata, SPSS, SAS, 
Splus, etc.) 
Statistical packages can be used for: 
 Analysis 
 Data Manipulation 
 Data Management
Open source statistical package 
 ADMB– a software suite for non-linear statistical 
modeling based on C++ which uses automatic 
differentiation. 
 ELKI - a software framework for development of data 
mining algorithms in Java. 
 Fityk – nonlinear regression software (GUI and 
command line) 
 gretl – gnu regression, econometrics and time-series 
Library
Open source statistical package 
Contd. … 
 JHepWork – Java-based statistical analysis framework for 
scientists and engineers. It includes an advanced IDE 
and Jython shell. 
 Octave – programming language (very similar to Matlab) with 
statistical features 
 Mondrian (software) - data analysis tool using interactive 
statistical graphics with a link to 
 OpenEpi – A web-based, open source, operating-independent 
series of programs for use in epidemiology and statistics based 
on JavaScript and HTML
Public domain statistical packages 
 Demetra+ 
 CSPro 
 Epi Info 
 X-12-ARIMA 
 BV4.1 
 GeoDA 
 MINUIT
Public domain statistical package 
 Winpepi – package of statistical programs for 
epidemiologists 
 ADAPA– batch and real-time scoring of statistical 
models 
 Analytica - visual analytics and statistics package 
 BMDP – general statistics package 
 CalEst – general statistics and probability package with 
didactic tutorials 
 DPS – comprehensive statistics package
Introduction to SPSS 
 SPSS (Statistical Package for the Social Sciences) is 
a statistical analysis and data management 
software package. SPSS can take data from almost 
any type of file and use them to generate tabulated 
reports, charts, and plots of distributions and 
trends, descriptive statistics, and conduct complex 
statistical analyses 
 This package of programs is available for both 
personal and mainframe computers
Features of SPSS 
it is easy to learn and use 
It includes full range of data management system and 
editing tools 
 it provides in depth statistical capabilities 
It offers complete ploting reporting presentation 
features
SIX DIFFERENT WINDOWS of SPSS 
 The Data Editor 
The Output Navigator 
The Pivot Table Editor 
The Chart Editor 
The Text Output Editor 
The Syntax Editor
 The Data Editor : 
The Data Editor is a spreadsheet in which you define your 
variables and enter data. Each row corresponds to a case while each 
column represents a variable. 
 The Output Navigator : 
The Output Navigator window displays the statistical results, 
tables, and charts from the analysis you performed. An Output 
Navigator window opens automatically when you run a procedure that 
generates output 
. 
 The Pivot Table Editor : 
Output displayed in pivot tables can be modified in many ways 
with the Pivot Table Editor. You can edit text, swap data in rows and 
columns
 The Chart Editor: 
You can modify and save high-resolution charts 
and plots by invoking the Chart Editor 
 Text Output Editor: 
Text output not displayed in pivot tables can be 
modified with the Text Output Editor. You can edit the output 
and change font characteristics (type, style, coluor, size). 
 The Syntax Editor : 
You can paste your dialog box selections into a 
Syntax Editor window, where your selections appear in the form 
of command syntax.
Advantages 
SPSS offers a user friendliness that most packages are 
only now catching up to 
GUI based program 
Quick descriptive statistics capability 
Most popular package in the social sciences 
Good for cluster analysis 
Runs on Windows, Linux, and Macintosh operating 
systems
Disadvantages 
Requires annual license 
Limited statistical procedures vs R or SAS 
Some procedures require purchase of add-on modules
WELCOME TO SPSS
Creating and Manipulating Data in SPSS 
 STEP 1: Defining Variables in a New Data Set 
 Variables are defined one at a time using the Define Variable dialog 
box. This box assigns 
 data definition information to variables. To access the Define Variable 
dialog box, 
 on the top of a column where the word var appears or select Define 
Variable from the Data menu 
Variable Name: This field describes the name of the variable being 
defined. To change the name, place the cursor in this field and type 
the name 
The variable name must begin with a letter of the alphabet and cannot 
exceed 8 characters. 
Spaces are not allowed within the variable name. Each variable name 
must be unique.
Thank you

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Presentation on spss

  • 2. Contents  Statistical package introduction  Statistical Packages  Introduction to SPSS  Features of SPSS  SPSS  EXCEL
  • 3. Statistical package introduction  It is a relatively easy package to learn.  Stata has an easy spreadsheet-style data representation  - Stata keeps good records of your actions.  - It is relatively cheap (both in cost and memory)  Stata license is perpetual – if you buy it, you own it forever.
  • 4. Statistical packages  There are many statistical packages (Stata, SPSS, SAS, Splus, etc.) Statistical packages can be used for:  Analysis  Data Manipulation  Data Management
  • 5. Open source statistical package  ADMB– a software suite for non-linear statistical modeling based on C++ which uses automatic differentiation.  ELKI - a software framework for development of data mining algorithms in Java.  Fityk – nonlinear regression software (GUI and command line)  gretl – gnu regression, econometrics and time-series Library
  • 6. Open source statistical package Contd. …  JHepWork – Java-based statistical analysis framework for scientists and engineers. It includes an advanced IDE and Jython shell.  Octave – programming language (very similar to Matlab) with statistical features  Mondrian (software) - data analysis tool using interactive statistical graphics with a link to  OpenEpi – A web-based, open source, operating-independent series of programs for use in epidemiology and statistics based on JavaScript and HTML
  • 7. Public domain statistical packages  Demetra+  CSPro  Epi Info  X-12-ARIMA  BV4.1  GeoDA  MINUIT
  • 8. Public domain statistical package  Winpepi – package of statistical programs for epidemiologists  ADAPA– batch and real-time scoring of statistical models  Analytica - visual analytics and statistics package  BMDP – general statistics package  CalEst – general statistics and probability package with didactic tutorials  DPS – comprehensive statistics package
  • 9. Introduction to SPSS  SPSS (Statistical Package for the Social Sciences) is a statistical analysis and data management software package. SPSS can take data from almost any type of file and use them to generate tabulated reports, charts, and plots of distributions and trends, descriptive statistics, and conduct complex statistical analyses  This package of programs is available for both personal and mainframe computers
  • 10. Features of SPSS it is easy to learn and use It includes full range of data management system and editing tools  it provides in depth statistical capabilities It offers complete ploting reporting presentation features
  • 11. SIX DIFFERENT WINDOWS of SPSS  The Data Editor The Output Navigator The Pivot Table Editor The Chart Editor The Text Output Editor The Syntax Editor
  • 12.  The Data Editor : The Data Editor is a spreadsheet in which you define your variables and enter data. Each row corresponds to a case while each column represents a variable.  The Output Navigator : The Output Navigator window displays the statistical results, tables, and charts from the analysis you performed. An Output Navigator window opens automatically when you run a procedure that generates output .  The Pivot Table Editor : Output displayed in pivot tables can be modified in many ways with the Pivot Table Editor. You can edit text, swap data in rows and columns
  • 13.  The Chart Editor: You can modify and save high-resolution charts and plots by invoking the Chart Editor  Text Output Editor: Text output not displayed in pivot tables can be modified with the Text Output Editor. You can edit the output and change font characteristics (type, style, coluor, size).  The Syntax Editor : You can paste your dialog box selections into a Syntax Editor window, where your selections appear in the form of command syntax.
  • 14. Advantages SPSS offers a user friendliness that most packages are only now catching up to GUI based program Quick descriptive statistics capability Most popular package in the social sciences Good for cluster analysis Runs on Windows, Linux, and Macintosh operating systems
  • 15. Disadvantages Requires annual license Limited statistical procedures vs R or SAS Some procedures require purchase of add-on modules
  • 17. Creating and Manipulating Data in SPSS  STEP 1: Defining Variables in a New Data Set  Variables are defined one at a time using the Define Variable dialog box. This box assigns  data definition information to variables. To access the Define Variable dialog box,  on the top of a column where the word var appears or select Define Variable from the Data menu Variable Name: This field describes the name of the variable being defined. To change the name, place the cursor in this field and type the name The variable name must begin with a letter of the alphabet and cannot exceed 8 characters. Spaces are not allowed within the variable name. Each variable name must be unique.
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