Intermediate Statistics Using SPSS

Name of the PhD course
Intermediate Statistics Using SPSS and R (spring 2022)

2-3 February, 2022
2-3 March, 2022
6-7 April, 2022
4-5 May, 2022
1-2 June, 2022

The start time on DAY 1 of each teaching block is 10:00-15:30 (2/2, 2/3, 6/4, 4/5, 1/6)
On DAY 2 of each teaching block the start time is 09:00-15:30 (3/2, 3/3, 7/4, 5/5, 2/6)

Aarhus University, Bartholins Allé 10 (building 1325) and Bartholins Allé 14 (building 1327)
Module 1 (2/2-3/2): Online teaching
Module 2 (2/3-3/3): DAY 1: 1325-440 (10:00-12:00) + 1325-136 (12:00-15:30). DAY 2: 1325-440
Module 3 (6/4-7/4): DAY 1: 1327-026. DAY 2: 1325-440
Module 4 (4/5-5/5): DAY 1: 1327-026. DAY 2: 1325-440
Module 5 (1/6-2/6): 1325-440

Some parts or modules on the course may be taught online.

Anne Scharling Rasmussen

Ali Amidi (AA), Anne Scharling Rasmussen (ASR), Kaare Bro Wellnitz (KBW) and Mia Skytte O’Toole (MSO) 


ECTS points
The course consists of five modules. In order to receive a certificate of completion and ECTS points for the course, participants must submit at least 1 homework assignment and attend at least 2 days of the course. The specific number of ECTS points awarded is determined as follows: 1 assignment + 2 days of attendance (one module) = 3 ECTS points; 2 assignments + 4 days of attendance (two modules) = 6 ECTS points; 3 assignments + 6 days of attendance (three modules) = 9 ECTS points, 4 assignments and 8 days of attendance (four modules) = 12 ECTS points, all 5 assignments + full attendance (all five modules) = 15 ECTS points.

Priority will be given to students who can attend the entire course, but it is possible to attend specific modules if spots are available. Notice that certification for a module only is awarded if the corresponding assignment is submitted and approved, and that no certificates are forwarded until the entire course is finished.

Course description
The aim of this course is to provide participants with a broad intermediate-level competence in carrying out common quantitative psychological analyses using IBM SPSS Statistics software, as well as to introduce a few subjects on more advanced statistics using IBM SPSS Statistics software as well as R.

Content: The course begins with a brief review of basic statistical concepts and tests followed by more detailed instruction on: (i) Multiple regression including mediation/moderation; (ii) Factorial ANOVAs, (iii) Logistic regression, (iv) Factor Analysis and Structural Equation Modelling; and (v) Multi-Level Modelling. Please note that this course assumes previous undergraduate knowledge of introductory statistics. It is recommended that if you need a brush-up, you review the suggested readings for the first two days of class before the course begins 

Format and Evaluation: The course includes a combination of lectures and practical instruction using SPSS and R software. Focus will be on giving participants hands-on experience with each type of analysis. Practical exercises will be assigned for each session; some of these exercises will be done collectively during the teaching day and others must be completed independently

Reading: The core recommended text for the course is Field, A. (2018). Discovering Statistics Using SPSS, 5th Edition. Sage Publications


Target group
PhD students in psychology

Applying for the course
Please complete the "online application form"
IMPORTANT: The course assumes basic knowledge of statistics, so participants must provide proof that they have completed at least one previous statistics course in order to be eligible to participate. Please use the space "Prior knowledge of the topic of this course" to describe accomplished (bachelor or master) statistics course(s), or please forward documentation by email to Anette Christensen ( Applicants who omit this information will not be admitted to the course

Deadline for applying: 31 December 2021
Applicants will be informed whether they have been given a spot on the course no later than on 7 January 2022; not before the above deadline for applying

Maximal number of participants
16 (priority will be given to students who can attend the entire course)