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Data Services Class Descriptions

Information, materials, and schedules for all currently offered Data Services classes

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Staffed Hours: Spring 2023
   Mondays:        12pm - 5pm
   Tuesdays:       12pm - 5pm
   Wednesdays: 12pm - 5pm
   Thursdays:     12pm - 5pm
   Fridays:          12pm - 5pm

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Stata is a software package for statistical analysis of data. This tutorial will introduce you to the basics of Stata and will cover importing, creating and editing data sets, and provide an overview of commonly used statistical procedures.

Computer workstations with Stata 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:

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:
  • Stata environment (Command Line, Do Files, Browse/Edit)
  • Changing the directory, setting a global macro
  • Importing data (manual entry, Stata files, Excel and CSV files)
  • Computing variables and labeling data
  • Recoding a continuous variable into a categorical variable and apply value labels
  • Descriptive statistics, frequency tables, cross-tabulation tables
  • Creating scatterplots, histograms etc...
  • Basic Analysis (t-test, chi-square, correlation, regression etc...)
  • Exporting regression output
Class Materials:


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