SPSS and SamplePower 3

In this free and practical self-paced training course, participants will learn how to use SPSS and SamplePower 3 software packages through practical application and hands-on exercises. This course does not teach Statistics, rather how to use SPSS Statistics and Sample Power 3 software to further research. A functional knowledge of graduate-level statistics is required.

Appropriate coursework examples:
STAT 6126 and STAT 6127
ALS 5932
EDF 6402
EDF 6403
HLP 6515
STA 6166


  1. Data preparation
  2. Exploratory data analysis
  3. Inferential statistics for the mean and the median
  4. ANOVA, Correlation  and bivariate linear regression
  5. Multiple and quantile linear regression
  6. Inferential statistics for the proportion
  7. Logistic regression
  8. Power analysis for each of the statistical tests

All modules are mandatory. All seven modules must be completed to earn the tutorial and the SPSS certificate.


The course will be offered from 01/16/24 to 03/15/24. Click on the registration button above to register. You will not receive a confirmation email after registration. The trainer will contact participants three weeks before the course starts. Registration deadline: 01/12/24 at 5:00 pm.

This training is open to faculty, staff, postdoctoral candidates, graduate students, and graduate assistants.

Undergraduate students interested in SPSS can complete the SPSS basic course with LinkedIn Learning, or contact Dr. David Schwieder (dschwieder@uflib.ufl.edu) at Library West for SPSS assistance.

Participants are encouraged to complete the "SPSS Statistics Essential Training" in LinkedIn Learning before the course starts.

We are also offering the SPSS Basic Statistical Analyses learning path in LinkedIn Learning as an alternative training source for basic statistical analyses.


  1. Participants must have taken at least a graduate statistics course not necessarily from the Statistics Department.
  2. Read SPSS Statistics & Sample Power Syllabus - Spring 2024 for more information.

Time Commitment

Online: Seven modules to complete from 01/16/2024 (8:00 am) to 03/15/2024 (5:00 pm). No extension will be granted!




Who's it for?

Faculty, Staff, TA / Grad Asst


Online: self-paced

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