About me: Dr Jens Roeser

  • associate professor in psycholinguistics @ psychology department (Nottingham Trent University)
  • module leader for PSYC40540 (confidential matters: jens.roeser@ntu.ac.uk)
  • research
    • Language production / comprehension / acquisition (e.g. Roeser, Torrance, and Baguley 2019; Roeser et al. 2025; Garcia, Roeser, and Kidd 2023)
    • Bayesian modelling (Roeser et al. 2024, 2025); keystroke logging; eye tracking
  • teaching:
    • 10 years of experience teaching data science and statistics to UG, PG students, academics and professionals (psyntur, Andrews and Roeser 2021)
    • cognitive psychology and language acquisition (Roeser and Wood 2019)

Who are you?

Go to menti.com

(cause lets keep things anonymous for now)

Elephants in the room

Some of you know more about statistics and R/RStudio than others.

Things might feel too fast or too slow.

For some students, statistics might feel stressful.

In our experience, students do not fail if they engage with the module.

Overview

Module Aims

  • Theoretical underpinnings of statistics used in psychology.
  • General linear regression models approach to statistics: focuses on the relationship between multiple linear regression, ANOVA and ANCOVA, and other models.

Delivery mode

  • Weekly pre-recorded lectures
  • Weekly 2hr in-class workshops every Friday, 3pm - 5pm.

Schedule

Week 1

  • Module overview
  • Introduction to R & RStudio

Week 2

  • Lecture: Introduction to statistical inference
  • Workshop: Exploring, summarising and visualising data with R

Weeks 3 & 4

  • Classical statistical inference (hypothesis testing)
  • From here onward, there will be online problem sets for you to answer

Weeks 5 & 6

  • Simple and multiple normal linear regression

Week 7

  • General linear models (categorical predictor variables)

Week 8

  • Varying slope, varying intercept, general linear models (ANCOVA)

Week 9: Revision session

Week 10: Exam

Assessment

  • Single 90 mins exam (approx. 30 questions)
  • Friday, 28 November, 2025, 2:30pm – 4pm (room will be available 2pm).
  • Questions will involve R, which can be used on personal laptops.
  • All questions will be multiple choice or short-answer.
  • Not open-book, but you may use 2 two-sided A4 pages of notes.
  • Normal exam rules apply: no collaboration or communication, no use of (online) resources.

Assessment criteria

Practical and theoretical understanding of all contents, in particular

  • nature of the statistical models
  • assumptions and the contexts in which the statistical models are applied
  • ability to perform analysis using RStudio
  • interpret the output of statistical analysis

Useage of GenAI

  • Please submit the Generative Artificial Intelligence (GenAI) Usage Declaration Form via Dropbox by 5 December 2025.
  • Use ChatGPT and others for your own learning, to generate code, to help you find errors in code etc.
  • But you must not use GenAI during the exam.

How to engage with this module?

  • Watch prerecorded lecture videos every week (before the workshop)
  • Attend workshops and participate in activities
  • Formative assessments (weeks 3 - 8):
    • Lecture learning-check quiz (after lecture)
    • Homework problem set (after workshop)
    • Mock exam
  • Support: Post questions / comments on MS Teams channel for both psyc40540 and psyc40545 (check if you have access).
  • Additional maths / statistics support is provided by NTU’s library.

Setting up R and RStudio

  • Installation
  • Installing tidyverse and psyntur
  • Explore RStudio environment

Setup an R-project

  • What it is: A special folder for your work in R.
  • What it does: Keeps your scripts, data, and results together.
  • Why it helps:
    • Sets the folder as your working directory automatically.
    • No setwd() headaches.
    • Easy to share or move your whole project.
  • Works well with Git/GitHub for teamwork and version control.
  • Everything for one analysis stays neatly in one place.
  • Create R Project for “psyc40540” with sub-directories: “data” and “exercises”.
  • Download the “exercises” folder from NOW (week 1 unit) and move the content to your R-project’s “exercises” folder

Introduction to R and RStudio

  • R-Scripts and executing code
  • Comments, commands, sections
  • Using R as a calculator
  • Variables and assignment (<-)
  • Vectors and combining vectors (c())
  • Base-R functions
  • Indexing ([1])
  • Booleans (TRUE, FALSE) and logical operators (|, &, >, <, ==)
  • Data types (numeric, character, factor, logical)
  • Coercing vectors (vectors are homogeneous)
  • Missing values (NA)
  • Data frames
  • Nested functions
  • Help pages
  • Reading in and viewing data

Reading recommendations

  • After the session, go through this introduction to R, even if you have used R before.
  • Andrews (2021) Doing Data Science in R: An Introduction for Social Scientists. LINK
  • Wickham and Grolemund (2016) R for data science. LINK
  • Field (2026) Discovering statistics using R LINK
  • Faraway (2015) Linear models with R LINK

References

Andrews, Mark. 2021. Doing data science in R: An Introduction for Social Scientists. London, UK: SAGE Publications Ltd.

Andrews, Mark, and Jens Roeser. 2021. Psyntur: Helper Tools for Teaching Statistical Data Analysis. https://CRAN.R-project.org/package=psyntur.

Faraway, Julian J. 2015. Linear Models with R. Vol. 2. CRC press.

Field, Andy P. 2026. Discovering Statistics Using R and RStudio. 2nd ed. London: SAGE Publications.

Garcia, Rowena, Jens Roeser, and Evan Kidd. 2023. “Finding Your Voice: Voice-Specific Effects in Tagalog Reveal the Limits of Word Order Priming.” Cognition 236: 105424.

Roeser, Jens, Rianne Conijn, E. Chukharev, G. H. Ofstad, and Mark Torrance. 2025. “Typing in Tandem: Language Planning in Multisentence Text Production Is Fundamentally Parallel.” Journal of Experimental Psychology: General 154 (7): 1824–54. https://doi.org/10.1037/xge0001759.

Roeser, Jens, Sven De Maeyer, Mariëlle Leijten, and Luuk VaWaes. 2024. “Modelling Typing Disfluencies as Finite Mixture Process.” Reading and Writing 37 (2): 359–84. https://doi.org/10.1007/s11145-023-10489-4.

Roeser, Jens, Mark Torrance, and Thom Baguley. 2019. “Advance Planning in Written and Spoken Sentence Production.” Journal of Experimental Psychology: Learning, Memory, and Cognition 45 (11): 1983–2009.

Roeser, Jens, and Clare Wood. 2019. “Language and Literacy.” In Essential Psychology, edited by P. Banyard, C. Norman, G. Dillon, and B. Winder, 3:197–226. London: Sage.

Wickham, Hadley, and Garrett Grolemund. 2016. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O’Reilly Media, Inc.