Week | Topic |
---|---|
1 | Introduction to Psychology as a Science |
2 | What is this thing called “Science”? |
3 | Approaches to Research |
4 | Introduction to study design |
5 | Open Science |
6 | Describing measurements I |
7 | Describing measurements II |
8 | Distributions |
9 | Transformation and comparisons |
10 | Visual summaries of data |
11 | Introduction to probability |
Lecture 1: Introduction to Psychology as a Science
Introductions and housekeeping
The aim of today’s lecture is to provide you with an overview of the structure of the research methods modules that you’ll be taking in your degree. I’ll also try to give you some tips that will help you to succeed in this course. Although this is not an inherently difficult course, a lot of the material you’ll be encountering may be new to you. Some of it might even seem a little intimidating (in particular, the programming that you’ll be doing in the practical classes). But if you stick with it, and give it your best shot, then I’m confident that you’ll be able to do well.
Introductions
The main teaching team for Psychology as a Science (PAAS) is made up of three people. Each of us has different roles and responsibilities. Knowing this will help you to know who to contact if you need help with something (but see more on knowing who to contact below).
Dr Lincoln Colling (lecture content convenor)
Dr Colling is responsible for the lecture content, and for preparing the final exam. The final exam will cover the topics covered in the main weekly lectures.
Dr Jenny Terry (practical content convenor)
Dr Terry is responsible for the content covered in the practical sessions, the R
homework activities, and the weekly R
assessments. She is also responsible for the lab report, the major piece of written work you’ll produce this year.
If you don’t know what R
is then don’t worry—99% of the people taking this course won’t know what R
is. But you’ll learn all about R
and RStudio
in the practical classes.
Dr Vlad Costin
Dr Costin, along with Dr Terry, is one of the lead practical lecturers.
Apart from these three people you’ll also get to meet Dr Bryan Singer, who will be the lecturer for the special ethics lecture in Week 6. There are also several doctoral tutors who will be helping out with the practical classes and who will also be responsible for marking the lab report.
Tips for doing well
The information that most of you will want to know is how to do well in this course, so we’ll get it out of the way right up the front. The single best thing you can do to do well in this course is to show up to class every week. Turning up in person every week not only means that you’ll get exposed to the lecture content, but you’ll also get to meet me, talk to me, meet your classmates, and talk to them too. So much of what makes university special are those moments that happen around the classes. And all you need to do to experience those moments is to show up to class every week.
Apart from showing up every week the other thing you can do is to do all the assessments. This is particularly important for the weekly assessments linked to the practical content. Each of these assessments builds on the one before, so if you fall behind it can be hard to catch up. Even if you find them difficult, you should still do them. They will get easier!
Start off by being present for everything and the rest will fall into place!
Finding the information you need
One of the most important things you need to know if you want to succeed in the course (and this is true of all the courses you’ll be taking) is how to find the information you need. The first place to look for any information is on Canvas. If you’re reading this lecture handout then you’ve probably already found Canvas. The Canvas page for this course will be your one-stop shop for almost all the information you need about this course. Familiarise yourself with it. Especially the front page! Click all the links, and read through the pages. If you have a question like “What do I do if I can’t make a practical or lecture?”, then that information is on Canvas. If you want to know what the assessments are for this course, then that will also be on Canvas. And If you want to know whether references are counted as part of the word count for your report, then that will be on Canvas too!
There’s a lot of information on Canvas. In fact, there’s probably too much information, and so it can be a little overwhelming. To help with this, I have two tips.
First, as I said above, click the links and read through all the pages. But while you’re doing this, keep a bit of paper or a notebook handy. Use this to note down bits of information, or where to find certain information, so you can check back when you need it. You can also bookmark pages that you think will be useful later. And when you bookmark a page you can give it an informative title that is meaningful to you. All this will help you find the information you need when you need it. And remember, on any web-page you can hit Ctrl F (windows) or Command F (mac) to search for a word. This is useful if it’s a long page with a lot of text, and you’re looking for something specific.
Second, check out the Frequently Asked Questions (FAQ). Here I will list the answers to some questions that I tend to encounter often. You might just find the answer to your question here. I will try to update this as I encounter more frequently asked questions, so make sure to check back whenever you’re stuck.
Knowing who to contact
One thing that is tricky when you’re first starting out at university is knowing who to contact with your queries. Here are some tips to guide you in the correct direction.
Admin queries
Admin queries are any queries than are not directly related to the course content. For example, if you’ve been absent from class, and you want to inform somebody, then that’s an admin query. If you’re meant to have an extension to hand-in date for an assessment, but it hasn’t been correctly applied, then that’s an admin query. If you’re unable to submit and assessment because you’re unwell, then that too is an admin query. All admin queries should be directed at the admin staff.
You can contact the admin staff by emailing them at psychology@sussex.ac.uk. If you’d specifically like to report an absence then you can psychologyabsence@sussex.ac.uk. For more information about Attendance and Absences, check out the page on Canvas.
Queries about course content
The lecturers are your point of contact if you have questions about the course content. Who you contact will depend on what section of the course your question covers:
For questions about lecture materials
If you have a question about material that was covered in one of the regular weekly lectures then the best person to get in touch with is me, Dr Lincoln Colling. I can also help with queries related to the final exam (because the final exam covers the material from the regular weekly lectures).
The best way to get in touch with me is to grab me right after the lecture. I’ll always hang around for a few minutes to answer questions. But if you need to run off then you can always book into a drop in session. To book into a drop in session, use the calendar on the front page of the module’s canvas site.
For questions about the practical content
If you have a question about something that was covered in one of your weekly practical sessions then the best person to contact would be the practical lead for your practical. This will either be Dr Jenny Terry or Dr Vlad Costin.
Your practical lead will also be able to help you out with queries about the weekly R
assessments.
The best way to contact Dr Terry and Dr Costin is to talk to them in your practical session.
For queries about the report
If you have queries about the report, then the best person to contact is Dr Jenny Terry.
For general R
help
If you have general R
and RStudio
queries, and you weren’t able to get them answered in class, then you can go to one of the R Drop in Sessions. You can go to any of the R Drop in Sessions, but try to go to one run by somebody that teaches on PAAS. To book into an R
Drop in session, use the calender on the front page of the module’s canvas site.
Module Discussion Board (Discord)
The course discussion board is run through Discord. To sign up to the course discord server use the following link https://discord.gg/TBf8Zju2xv
You may sign up under an alias so that you can ask your questions anonymously, if you prefer.
The Discord server will be checked regularly, but is not moderated 24/7. If anyone spots anything that could be deemed inappropriate, please tag the teaching team. Inappropriate posts will be removed, as will any repeat offenders.
Research methods in Psychology
Psychology as a Science is the first of a series of research methods modules that you’ll take during your psychology degree.
Following this module, you’ll take the following modules:
Analysing Data (next term)
Discovering Statistics (year 2)
Quantitative and Qualitative Methods (year 2)
These courses build up to prepare you for your research dissertation in the final year. But they’re also a great way to learn a lot of transferable skills that are useful outside university, for example: how to analyse data, how to make sense of statistics, and computer programming/coding skills.
Psychology as a Science (PAAS) covers an introduction to the research process. Some topics you’ll cover include:
Introduction to Philosophy of Science
Different approaches to research including quantitative methods and qualitative methods
Basics of statistical theory
We’ll also introduce you to coding in the R
programming language. You’ll cover the basics of the R
language, how to process and summarise data, and how to make plots in R
. Along the way we’ll work with some of the same data that you’ll be using for your Cognition in Clinical Contexts lab report.
In Analysing Data (AD) you’ll learn about the core statistical tests used in Psychology. You’ll also cover more advanced use of R
, and you’ll learn how to perform statistical tests in R
. AD will also give you your first chance to independently analyse some data.
In Discovering Statistics (DS) you’ll learn even more advanced statistical tests, and more in-depth knowledge of R
.
And in the final course, Quantitative and Qualitative Methods (QQM) you’ll learn about advanced multivariate statistical techniques. But you’ll also learn about non-statistical approaches such as interviews and discourse analysis.
The work you do in these modules will also connect up with other modules:
Analysing Data with, for example, Psychobiology
Discovering Statistics with, for example, Developmental Psychology
And Quantitative and Qualitative Methods with, for example, Social Psychology
Research methods does not happen in isolation, but it’s connected with everything else you do in your degree.
Why research methods?
The dominant approach to training psychologists is the scientist practitioner model. Doing research is integral to this approach! Just like medical doctors, who not only deliver treatments but also develop treatments, psychologists also apply and produce knowledge. As a psychologist you want to do what works and being able to read, critique, and conduct research will help you know what works and allow you to develop evidence-based care.
Even for those that don’t become psychologists, research methods is still useful and the skills you’ll learn in your research methods courses will prepare you for careers in a range of industries. These might include working as a data scientist, working in consultancy, or working in the civil service and government.
Structure of this module
Like most research methods modules PAAS is made up of three main activities:
Weekly lectures
One hour each week.
Covers research methods, statistics, and theory
Note that you’ll also have a special lecture one evening in Week 6 that will cover research ethics. Check your timetable!
Tutorials/Practical preparation homework
About an hour a week.
Done in
R
as preparation for the practical class.
Practical classes
Two hours a week.
Gives you hands-on experience with the
R
programming language.
You’ll find out more about the exact structure of the tutorials and practicals in the practical sessions.
Assessment Structure
For the assessment there’s a 50/50 split between coursework and the exam.
The coursework is made up of four parts. Pay special attention to this section, because the list on Sussex Direct can be a little confusing.
Computer Based Exam worth 10% due in approximately Week 8
This will cover the material from the ethics lecture in Week 6
Computer Based Exam worth 40% (see below about due date)
This refers to the
R
assessments that you’ll do. You’ll find out more about these in the practical classes. It’s very important to note that this isn’t a single assessment due at the end of term. Rather these consist of several assessments you’ll do through out the term. Make sure you keep up with them, because doing them will help you achieve a good grade.Report worth 40% due in approximately Wk 9
Portfolio with 10% (listed on Sussex Direct as due in Wk 11)
This refers to the 20 credits worth of research participation that you’re required to do as part of the course. To find out more about this follow the big yellow link labelled Research Participation/Sona.
The due date is the final day you can complete research participation. But don’t wait until the last week to do it, because there’ll probably be no studies left to take part in. These are easy marks so don’t miss out on getting them. Doing research participation is also important for your academic development, because it will give you a first-hand experience of the research process.
Lecture topics
The rough outline of the lecture schedule is as follows:
The first set of lectures will cover big picture ideas. These lectures will probably be most useful in helping you to prepare for the report.
In these lectures we’ll talk about issues like:
What are scientific theories?
What issues do we need to consider when we’re measuring phenomena?
What does it mean to operationalise our variables?
What are different approaches you can take when conducting a study?
What are some sources of bias in psychology studies and publishing of psychology studies, and how might we be able to ameliorate some of these biases?
The second set of lectures are all about preparing you for learning about statistics and working with data.
In these lectures you’ll learn the underlying theory of statistical testing. You’ll learn how to reason about statistics and data, and the relationship between scientific hypotheses and statistical hypotheses.
Doing statistics isn’t like following a recipe. It’s not about just picking the “correct” statistical test out of a list. It involves thinking about what you want to know, why you want to know it, and how statistics can help you to know it. So we spend a bit of time this term just learning about this reasoning before you actually learn about statistical tests next term.
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