DAPR2

DAPR2

Welcome

Thank you for your interest in the Data Analysis for Psychology in R 2 (DAPR2) course! We welcome you to this course and hope that you will enjoy learning how to answer research questions of interest from real-world data. 

DAPR2 is a second course in data analysis for psychological research, using the R software. This course will introduce you to statistical modelling beyond what is typically taught in an introductory statistics course, empowering you with tools to analyse richer data and answer a broader set of research questions of interest to you. 

This course will play a key role in your future development as a researcher, giving you the skills and steps required to answer many questions of interest. 

Prerequisites

Students would benefit from having taken an introductory course in data analysis, such as DAPR1, or any other introductory statistics course. 

If you are an international student who did not take an introductory university course in statistics but took an AP statistics course in high school, you are well prepared and we would love to have you in this course! 

Content overview

This course introduces students to statistical modelling. Building up from the basic concepts learned in an introductory data analysis or statistics course, such as DAPR1 or AP statistics, students will refresh the main terminology of data analysis and t-tests. They will be introduced to simple and multiple linear regression. Particular attention will be put into categorical variables and experimental design as they play a special role in psychological research. Finally, the course will introduce simple and multiple logistic regression, Simpson’s paradox, and will compare the chi-square test and the logistic regression model for the analysis of two-way tables. 

Course commitment

Students are expected to attend 3 hours per week of taught sessions: 

  • 2x 1hour lecture 
  • 1x 1hour lab  

In addition, students will be given: 

  • a weekly homework quiz (part of the assessment), 
  • assigned reading, and 
  • there may be some work left over from your labs. 

In total, it is anticipated that students spend approximately 5-6 hours a week on DAPR2 work (inclusive of 3 compulsory hours). More information about how to structure your time can be found in the course Study Guide on LEARN. 

Assessment

The 20 weeks of teaching will be split into:  

  • 2 practice quizzes  
  • 18 graded quizzes (10% of final grade)  
    Notes: only the 14 best scores out of the 18 quizzes will count towards the final grade.  

Furthermore, there will be: 

  • graded reports (90% of final grade, 2x 45% each)
    Notes: one report per semester.

Course team

Dr Tom Booth

Dr Alex Doumas

Dr Josiah King

Dr Umberto Noè

How to approach your data analysis training

Try to keep up with course material, be inquisitive, and do not be afraid to ask questions. You will love this course as you will then have the skills to answer a broad range of research questions.

It is really important that you establish good working patterns for DAPR2 course early. It will help you throughout the rest of your degree.

The DAPR2 course has been structured to encourage continual engagement, based on the fact that these types of skills are best acquired through regular practice. We strongly encourage students to work together week by week in labs, problem sets, and working through lecture material, and to make use of the drop-in sessions provided. These are your chance to come and clarify any points of misunderstanding with the teaching team while it is all still fresh in your mind. Working with friends, sharing ideas, explaining concepts, and discussing with the teaching team are all highly effective tools for learning. We hope we can build an atmosphere that will encourage these things.