2.  Overview of SPSS  Interface  Getting Started  Managing Data  Descriptive Statistics  Basic Analysis  Additional Resources

3. NYU Data Services  Tutorials and support for academic software  One-on-one consultation by appointment  Data Services website: –http://nyu.libguides.com/dataserviceshttp://nyu.libguides.com/dataservices –Google “nyu data services”Google “nyu data services”  Training tab –Slides and sample code –External resources

4.  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

5.  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

6.  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.

7.  Recoding Variables: Can be necessary in several cases: - reverse coded items - continuous variables into grouping variables - grouping variables in OLS  Computing Variables

8.  For variable’s description: Analyze -> Descriptive Statistics -> Descriptives  For frequencies: Analyze -> Descriptive Statistics -> Frequencies  To detect outliers: Analyze -> Descriptive Statistics -> Explore

9.  Scatter Plot: Graphs -> Legacy Dialogs-> Scatter/dot  Histograms: Graphs -> Legacy Dialogs-> Histograms  OR Analyze -> Legacy Dialog

10.  Some examples: Correlation Analyze -> Correlate -> Bivariate T-tests Analyze -> Compare Means -> Regression Analyze -> Regression-> Linear ANOVA Analyze -> General Linear Models

11. Additional Help  The Data Services staff is available to answer SPSS related questions. –Email: data.services@nyu.edu –Phone: (212)-998-3434 –Location: 5 th Floor of Bobst Library  Please refer to the Data Services training pagetraining page

12.  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