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SPSS for Beginners - Basics, Data Analysis & APA Tables
Bestseller
Highest Rated
Rating: 4.8 out of 5(23 ratings)
141 students
Last updated 6/2025
English

What you'll learn

  • Run, interpret and report the 5 most popular statistical techniques in SPSS correctly
  • Create perfect APA style tables for these analyses with very little effort
  • Work with real-life data files and detect and fix common problems such as missing values, outliers and string variables
  • Perform a wide variety of SPSS tasks with syntax and deliver complete and well-documented projects to your instructors or clients

Course content

6 sections26 lectures14h 1m total length
  • SPSS - Quick Introduction & Overview Main Features19:43

    Explore SPSS basics—from the data editor window (data view and variable view) to syntax, import data formats, and APA-style outputs.

  • Quick Course Overview10:50

    Explore SPSS basics, customization, and time-saving tools, master data preparation and the big five statistical tests, and learn APA reporting for accurate table styling.

  • Which Lectures Do You Need?9:18

Requirements

  • A laptop with a normal keyboard (no tablet or smartphone)
  • SPSS (possibly a free trial version), preferably version 27 or higher
  • A spreadsheet editor, preferably Excel or otherwise Libreoffice or Googlesheets
  • Very basic knowledge of statistics (measurement levels, mean, standard deviation, ...)

Description

In this course, you’ll learn everything you need to know for successfully completing data analysis projects in SPSS (“IBM SPSS Statistics”).


Whether you’re a Bachelor’s or Master’s student working on your thesis or a professional in market research, this course will show you how to get things done in SPSS the right way.


This starts off with mastering some fundamentals such as


  • the basics, tips & tricks for the data editor, syntax and output windows;

  • how to paste, run, edit & save SPSS syntax and why even do so in the first place;

  • how to screen your data file and fix any issues you may encounter?


Most other SPSS courses completely ignore these fundamentals and use only nicely prepared, problem-free data files. Sadly, this doesn’t prepare you for working with real-life data because these usually contain issues such as


  • missing values

  • string variables

  • outliers

  • reverse coded variables

  • long variable names and absence of variable and/or value labels.


In this course, you’ll quickly learn how to detect and fix any data complications the right way before you proceed to the actual data analyses.


After this data preparation section, I’ll cover the 5 most sought-after statistical analyses (the “big 5 statistical tests”) which are


1. the chi-square independence test

2. the independent samples t-test

3. ANOVA (analysis of variance)

4. (Pearson) correlations

5. multiple linear regression analysis.


You’ll learn how to run, interpret and report each of these tests correctly and completely. In contrast to most other courses, I’ll also cover


  • which test is suitable for which research question;

  • how to evaluate if you meet the assumptions required for each test;

  • which effect size measures are applicable with Cohen’s (1988) rules of thumb for small, medium and large effects

  • how to visualize the major trends in your data with charts.


After successfully running some test(s), you may need to report your results in APA style. In this course, you’ll learn how to create perfect APA tables with minimal time and effort by using


  • some handy SPSS tools & tricks for getting the right table contents and layout;

  • Excel or Googlesheets for styling your tables (numeric formats, alignment, row heights);

  • WORD or GoogleDocs for column widths, titles and final reporting.


Are you looking for the one course that shows how to deliver outstanding SPSS work with minimal time and effort?


Look no further.


See you in the course!


Ruben (founder, SPSS tutorials)

Who this course is for:

  • University students (bachelor's, master's or PhD) who need to write their theses
  • Professionals in fields such as market or policy research
  • Researchers working in a wide variety of governmental institutions