SPSS Bootcamp

Hands-on SPSS Training in NYC

This 3-day SPSS training concentrates on the most common topics that researchers use.

Learn to create a data file and enter data, conduct preliminary analyses, use graphs to describe and explore the data, manipulate the data, check the reliability of a scale, apply correlations, conduct significance tests, and perform regression analysis.

This class is perfect for those conducting quantitative research, analyzing big data and to those who want to use SPSS more effectively. We are proud to have one of the best SPSS instructors in the country.

SPSS Bootcamp

$999 21 Hours 185 Madison Avenue, NYC In-person classroom training

Register for a class

Dec 28–Jan 11 Fri, 10am–5pm
Feb 8–22 Fri, 10am–5pm
Mar 22–Apr 5 Fri, 10am–5pm

Corporate training available

Call 212-658-1918 or email us

What You'll Learn

  • Creating data files and entering data
  • Preliminary analyses
  • Manipulating the data
  • Correlations
  • Significance tests
  • Regression
  • icon for small classesSmall classes
  • icon for small classesComputer provided
  • icon for small classesBook included
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Full Course Syllabus

Download PDF Outline

Getting Started

  • Getting to know SPSS
  • Starting SPSS

Working with data files

  • SPSS windows
  • Menus
  • Dialogue boxes
  • Closing SPSS
  • Getting help

Creating a data file and entering data

  • Defining the variables
  • Entering data
  • Modifying the data file
  • Data entry using Excel

Preliminary Analyses

  • Descriptive Statistics
  • Frequencies (categorical variables)
  • Central tendency, standard deviations, and range (continuous variables)

Using graphs to describe and explore the data

  • Histograms
  • Bar graphs
  • Boxplots
  • Line graphs
  • Editing a chart/graph
  • Graphs using Excel

Manipulating the data

  • Calculating total scale scores
  • Transforming variables
  • Collapsing a continuous variable into groups

Checking the reliability of a scale

  • Procedure for checking reliability
  • Interpreting the output from reliability


  • Pearson product-moment correlation
  • Interpretation of output from correlation

Significance Tests

  • T-tests
  • Independent t-tests
  • Interpreting the output from independent t-test
  • Paired t-tests
  • Interpreting the output from paired t-test
  • Chi-square test of independence
  • Interpreting the output from chi-square test

Continuing with significance tests

  • Analysis of Variance
  • One-Way between-groups ANOVA
  • Post-hoc comparisons
  • Interpreting the output from one-way ANOVA
  • Two-Way between-groups ANOVA
  • Interpreting the output from two-way ANOVA
  • One-Way Repeated measures ANOVA
  • Interpreting the output from repeated measures ANOVA


  • Multiple linear regression
  • Interpreting the output from multiple linear regression
  • Logistic regression
  • Interpreting the output from logistic regression