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° 2024M1SPSS EN
Tags: Data Analysis


Originally SPSS was an acronym that stood for 'Statistical Package for the Social Sciences'. In the meantime, the software package has evolved into SPSS Statistics and one of the most used statistical packages in the world. The power and therefore the danger of SPSS Statistics lies in its ease of use. The syntax that allows you to apply a whole range of operations and statistical techniques to your data is covered by a relatively accessible graphical user interface that allows you to 'do statistics' without specialized programming knowledge and without much knowledge of statistics.

This course gives you a solid foundation to translate your own research questions into a qualitative data file and to further develop your SPSS skills based on your analysis needs. The introduction is designed to be experience-oriented. The participants are confronted with a number of problems after which possible solutions are discussed and demonstrated.

Target audience

This introduction is aimed at all persons who collect and/or store data with the intention of statistically analyzing and interpreting it.


Table of content:

Chapter 1: Getting started

  • Installing (trial version) and opening SPSS
  • SPSS Data, Output and Syntax windows
  • SPSS file menus
  • Getting help in SPSS

Chapter 2: Importing Data

  • Manually inputting data in SPSS
  • Import and open .xlsx, .csv, .txt, .sav, .dta and other file formats
  • Data and Variable views

Chapter 3: Data Manipulation

  • Select Cases
  • Sorting of Cases
  • Visual Binning
  • Data Merge
  • Splitting data

Chapter 4: Manipulating Variables

  • Creating New Variables
  • Recoding into Different Variables
  • Recoding into Same Variables
  • Summarisation of Data
  • Measurement Scales

Chapter 5: Exploring data

  • Frequency Tables
  • Descriptive Statistics
  • Generating a Histogram
  • Generating Statistics
  • Building Graphs Easily
  • Cross Tables

Chapter 6: Statistical Analysis

  • Hypothesis Testing
  • P-Value
  • Significance Levels
  • Confidence Intervals
  • T-Tests
  • Correlation Analysis
  • Linear Regression
  • Simple Linear Regression
  • Multiple Linear Regression

Exam / Certificate

There is no exam associated with this module. If you attend all classes, you will receive a certificate of participation by email at the end of the course.

Type of course

This is an hybrid course. The first lesson is on campus, the other 2 lessons online.


Thursday 3rd October2024, on campus,

Thursday 10th October 2024, online

Thursday 17th October 2024, online

From 5.30 pm to 9.30 pm


Faculty of Science, Campus Sterre, Krijgslaan 281, 9000 Ghent, building S1, 3th floor, Classroom 3.3


The participation fee is 540 EUR for participants from the private sector. Reduced prices apply to students and staff from non-profit, social profit, and government organizations

  • Industry, private sector, profession*: € 540
  • Non profit, government, higher education staff: € 405
  • (Doctoral) students, unemployed: € 325

*If two or more employees from the same company enrol simultaneously for this course a reduction of 20% on the course fee is taken into account starting from the second enrolment.


To register, add the course below to your shopping cart and proceed to checkout.

Is this your first registration for a Beta Academy course? In that case, you will need to create an account first. Afterward, you will receive a confirmation email to activate your account on the academy platform. You do not have to click on the activation link but can immediately return to your shopping cart to complete your course registration. If you do not receive a confirmation email for your course order, please contact our Science Academy at ipvw.ices@ugent.be.

Are you currently on the Nova-academy website? To proceed with the registration, simply click on the "More information" box located on the left side.

UGent PhD Students

Doctoral School pays for your course on the condition hat you sign the attendance list for each lesson. If you are absent, please notify our academy in advance by email and provide the necessary documents.

We follow the No Show polity of the Doctoral School!


Information on "KMO-portefeuille":https://www.ugent.be/nl/opleidingen/levenslang-leren/kmo


Science Academy

Faculty of Science



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