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Data Services Class Descriptions

Information, materials, and schedules for all currently offered Data Services classes.
This session covers data management techniques such as merging, reshaping, and aggregating datasets used in preparing data for analysis.
Software:

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/downloading the software prior to the tutorial.

Duration: 90 min

Room description:

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:
Skills Taught / Learning Outcomes:
  • Sorting Data
  • Creating Data Subsets
  • Splitting Output
  • Creating Custom Tables
  • Aggregating Data
  • Reshaping Data Sets
  • Merging Data Sets
  • Analyzing Multiple Response Sets
  • Working with Variable Sets
  • Creating Dummy Variables
  • Manipulating Dates
Class Materials:
 

Datasets

Material Preview 

Related Classes:

Data Visualization with Tableau

Data Cleaning Using OpenRefine

Introduction to Research Data Management

Introduction to R

Additional Training Materials: guides.nyu.edu/spss
Feedback: bit.ly/feedbackds

Upcoming sessions for this tutorial