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Saturday, November 24, 2012

Overview of SPSS

This is an overview of the SPSS program. In this clip we will discuss how to open an SPSS program, what items are in the SPSS menu bar, what you can do with the Data editor toolbar buttons and how to exit SPSS. The version for this online workshop is based on SPSS 16.0.

To open SPSS, double click on the SPSS icon on the desktop (if there is one) or go to the start menu, programs, SPSS and click on SPSS 16.0.When you first log into SPSS this is the dialog box that opens up. You have several options; you can run the tutorial guide, get a blank data window and type in your own data, open the database wizard to import an excel file, open an existing SPSS file, or any other file such as the journal file. In this case we will open an existing file. Here, the rows are cases and the columns are the variables.

Click on the following movie clip to see  Overview of SPSS:

MOVIE: Overview of SPSS

SPSS WINDOWS

There are a number of different types of windows in SPSS.   The window in which you are currently working is called the active window.   Some of the frequently used windows are:

Data Editor Window:  It displays the contents of the data file.   This is the window that opens automatically when you start an SPSS session.  In this window, you can create new data files or modify existing ones. When you open more than one data file, each data file has a separate Data Editor Window. The Data Editor Window provides two view of the data: 
  • Data View: It displays the data values. Each variable is a column. Each row is a case. 
  • Variable View: It displays a table consisting of variable names and their attributes. You can modify the properties of each variable or add new variables or delete existing variables in the Variable View Window.

Viewer Window:  It displays statistical results, tables, and charts.  This window opens automatically the first time you run a procedure that generates output.

Pivot Table Editor: It displays the results in pivot tables. To open this window, right click on the table, go to edit content and select “In separate window”. Alternatively, left click on the table and go to Edit Menu. Select edit content and then in separate window. You will be able to modify the table. 

Chart Editor Window:  This window is used to edit high-resolution charts and plots. 

Text Output Editor Window: This is used to modify text output that is not displayed in pivot tables. To open the window, right click on the text output, go to edit content and select “In separate window”. You will be able to modify the text output.

Syntax Editor Window:  It displays the choices made in the dialog box in the form of command syntax.  These commands can be edited and run to get some output.  You can also copy an old SPSS program here and run it.




Many tasks in SPSS are performed by selecting appropriate "pull-down" menus.  Each window in SPSS has its own menu bar with appropriate menu selections and toolbars.  The Analyze and Graphs menus are available in all windows.  Here are some Data Editor window menus and their uses:

File Menu: From the file menu you can open several different existing files or a database file such as an excel file or read in a text file. You can also save any changes to the current file.
   
Edit Menu: from the Edit menu,  you can cut, copy, paste, insert variables, insert cases, or use find in the Data Editor window.

Data Menu: The data menu allows you to define variable properties, sort cases, merge files, split files, select cases and use a variable to weight cases.

Transform Menu: The transform menu is where you will find the options to do some computations on variables, to create new variables from existing ones or recode old variables.

Analyze Menu: The analyze menu is where all statistical analysis takes place. From descriptive statistics to regression analysis to nonparametric tests.


Graphs Menu: The graph menu is where you can create high resolution plots and graphs to be edited in the chart editor window or you can create interactive graphs.

Utilities Menu: The utilities menu is used to display information on the contents of SPSS data files or to run scripts.


Add-Ons Menu: From the add-ons menu you can run other packages like conjoint, classification trees, or Neural Networks. Also there are programmability extensions that allow you to integrate programs like R and Python into SPSS. But you should keep in mind that if you want to run any of the add-ons listed here you will have to purchase them separately.

Window: From the window menu you can change the active window. The window with a check mark is the active one. In this case it is the data editor window.

Help: The help menu allows you to get help on topics in SPSS or to ask the statistics coach some basic questions.

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SPSS On-Line Training Workshop

Learn SPSS 16.0
Its a comprehensive & flexible statistical analysis and data management solution. 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. SPSS is available from several platforms; Windows, Macintosh, and the UNIX systems.

To Watch Videos Click Subheadings.

Overview of SPSS

Overview of SPSS


Getting Started

Getting Started


Options to personalize SPSS Interface

Options in the Edit Menu


Data Editor Window

Open Files in SPSS
Define/Modify Variables
File Manipulation: sort, merge, Transpose
File Manipulation: select, spit
Programmability Extension-Using R inside Spss


Data Trasformation

Transformation Of Variables
Data Restructuring between cases and variables


Output Windows

Output: editing, printingOutput: pivot table, saving,Exporting


Syntax Editor Window

Syntax Editing and Journal Files


Chart Editor Window

Output: Chart Editing


Statistical Technique

Introduction to statistical Procedures in SPSS


Descriptive Statistics

Frequencies and Descriptive
Explore Procedures
Crosstabs Procedures


Compare Means

T-Test Procedures
One-Way ANOVA


Genearal Linear Models

Univariate GLM
Multivariate GLM
GLM: Repeated measures


Generalized Linear Models

Generalized Linear Models


Mixed Models

Mixed Models


Bivariate Correlations

Bivariate and Partial Correlation


Regression Models

Linear Regression - stats,diagnosis,plots
Linear Regression - Variable selections
Logistic Regression


Log-linear Models

General Log linear models


Classification

Cluster Analsis - Clustering Variables or cases


Data Reduction

Factor Analysis


Scale - Reliability Analysis

Reliability of Analysis


Nonparametric Techniques

Nonparametric Runs and 1-sample
Nonparametric Independent Samples
Nonparametric Related Samples


 Time Series

Time Series Smoothing
Time Series: ARIMA models using Expert Module


 Survival Analysis

Kaplan Meier Models
Cox Regression Models


Quality Control

X-Bar, R Charts for Variable Data
p, np Charts for Attribute Data
c and u charts for Count Data
Capability Analysis


Receiver Operating Characteristic Curve

ROC Curve for Classification Model Comparison

 

Data Set Used

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