Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Data Services Class Descriptions

Information, materials, and schedules for all currently offered Data Services classes
SPSS is a software package for statistical analysis of data. This tutorial will introduce you to the basics of SPSS and will cover importing, creating and editing data sets, and provide an overview of commonly used statistical procedures.

Computer workstations with SPSS installed are available for in-person tutorials in Bobst 617. For remote tutorials, while some patrons decide to approach tutorials as a demonstration of the software, other patrons approach tutorials with a more “hands-on” approach and wish to interact with the software during the tutorial. If the latter is the case, we recommend referencing our supported software page for additional information on accessing the software prior to the tutorial.

Duration: 90 min

Room description:

As our global pandemic continues, some tutorials are held remotely and require NYU sign on to access, while others are held in person, without a remote component. Please note the correct modality and location of the tutorial when registering

Prerequisites: Basic computer literacy, understanding files and folders
Skills Taught / Learning Outcomes:
  • SPSS windows and layout (Data View, Variable View, Dataset, Output, Syntax windows)
  • Importing data from CSV and Excel files
  • Preparing data for analysis (value and variable labels, variable types, designating missing values)
  • Recoding variables (creating categories, automatic recoding, reverse coding)
  • Computing and transforming variables
  • Subsetting datasets
  • Descriptive statistics, frequency tables, cross tabulation tables
  • Creating histograms, bar charts, scatter plots etc...
  • Basic analysis (t-test, chi-square, correlation, ANOVA, regression)
  • Exporting output
Class Materials:

Dataset in CSV format.csv

Dataset in Excel format.xlsx

Dataset in SPSS format.sav

Material Preview.pdf 

Related Classes:

Data Visualization with Tableau

Data Cleaning Using OpenRefine

Introduction to Research Data Management

Introduction to R

Additional Training Materials:

Upcoming sessions for this tutorial