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Introduction to SPSS
Outline
Overview of SPSS Interface Getting Started Managing Data Descriptive Statistics Basic Analysis Additional Resources
NYU Data Services
Tutorials and support for academic software One-on-one consultation by appointment Data Services website:
– http://nyu.libguides.com/dataservices– Google “nyu data services”
Training tab– Slides and sample code– External resources
Overview of SPSS
SPSS is a statistical package that allows advanced data analysis, management, and graphics.
SPSS has capabilities similar to Stata, SAS, Minitab
There are SPSS student licenses available at NYU computer store for Windows and Mac.
You can also access it through VCL (vcl.nyu.edu) or using NYU computers
Getting Started: SPSS Files
Data file (.sav)
Syntax File (.sps) Commands should be written and saved in syntax rather
then using SPSS drop down menu:
Some advantages to using syntax files:
o allows reusing commands (the same analysis can be quickly repeated on different data sets as long as the variables name match)
o allows to copy, past and edit commands
o easier to read complex expressions
o allows sharing commands / methods with other researchers
Getting Started: SPSS Files
Output (.spv)
o Allows saving both the outcomes of our analysis but can also help retrieve information for further use in a syntax window.
o A bit messy – if we are running the same analysis but for example excluding some cases/ outliers it might be a little difficult to keep track of what is what.
Managing Data
Recoding Variables:
Can be necessary in several cases:
- reverse coded items- continuous variables into grouping
variables- grouping variables in OLS
Computing Variables
Descriptive StatisticsFor variable’s description:
Analyze -> Descriptive Statistics -> Descriptives
For frequencies:
Analyze -> Descriptive Statistics -> Frequencies
To detect outliers: Analyze -> Descriptive Statistics ->
Explore
GraphsScatter Plot:
Graphs -> Legacy Dialogs-> Scatter/dot
Histograms:
Graphs -> Legacy Dialogs-> Histograms
OR Analyze -> Legacy Dialog
Basic Analysis
Some examples:
Correlation Analyze -> Correlate -> BivariateT-tests Analyze -> Compare Means -> Regression Analyze -> Regression-> Linear
ANOVA Analyze -> General Linear Models
Additional Help
The Data Services staff is available to answer SPSS related questions.– Email: [email protected]– Phone: (212)-998-3434– Location: 5th Floor of Bobst Library
Please refer to the Data Services training page
Tutorial Evaluation
Please follow the link below: This will only take a few minutes and
help us a great lot in improving the tutorial
bit.ly/IntroSPSS