Psyconnect Statistics Guide

Preface

A common aversion faced by psychology undergraduates around the world is the need to study statistics. Given the relative infancy of psychology compared to other hard science fields or even the humanities, it is imperative that we as psychologists are able to read, comprehend and incorporate the most recent research as part of our continuous learning journey. With strong statistical foundations, one would be able to discern sound and rigourous statistical analyses from misleading or erroneous methods used in a fair percentage of psychological research (Bakker & Wicherts, 2011).

In some universities, the compulsory statistics modules are taught by mathematics professors. This is logical given their area of expertise, although it may further exacerbate the "expert blind spot" effect (Nathan & Petrosino, 2003). As experts, professors perform many abstract and symbolic reasoning steps automatically, "jumping" from one train of thought to another seamlessly as they would perceive. However, as undergraduates attempting to learn these concepts from scratch, it is exceptionally difficult to be able to "see" these connections automatically or even at all. Additionally, as psychology majors, certain "mathematical connections" inculcated in students majoring in fields requiring substantial mathematical foundations (e.g. engineering, computer science, mathematics) would be difficult to develop in short duration. What professors feel is trivial and does not require explicit instruction then, is what leads to students falling through the cracks.

In the case of my university (Singapore University of Social Sciences), the psychology program is fully part-time. The typical student profile then consists of mid-career switchers, mature adults and others who have gone years since their last interaction with mathematics. Assuming one leaves the education system with a GCE "O" Levels at 16 years old and pursues a non-mathematically heavy diploma in a polytechnic, it would be 6 years (!) before one can enrol in a part-time course with 2 years of working experience at 22 years old. That is akin to spending 6 years in a sedentary lifestyle with minimal exercise, making it difficult to return to a certain level of fitness.

What this book is for

This book serves to hopefully bridge the gap between expert knowledge and novice learning. Content will first focus on topics expected of students at "O" Levels, following the syllabus document published by the Singapore Examinations and Assessment Board. Afterwards, topics related to or typically required to understand statistical concepts at the undergraduate level will be discussed. \newline

By attempting to keep technical jargon to a minimum, this book should require minimal effort to comprehend. It would also provide a sort of "warm-up" for students' minds to prepare them to think mathematically, serving as pre-reading before they embark on their statistics modules.

What this book is for myself

My handwriting is terrible. When I first started my statistics modules, I needed a way to write my notes such that they were at least legible and easily written (i.e. typed out because I'm lazy). I was already using Notion to develop my own notes for my psychology modules and a quick google bestowed upon me the masterpiece that is $\LaTeX{}$. Notion allowed me to typeset mathematical formulae with $\LaTeX{}$ commands and what followed was the development of my summary notes that were shared to my fellow psychology peers.

This book is then a personal project for me to further develop my skills in working with $\LaTeX{}$, from typesetting everything within the document, learning the uses of various packages (TikZ, tabulary, BibTeX etc.) to creating my own graphics and figures in $\LaTeX{}$.

Todo

Code-related

• Ensure all code conforms to a single style (e.g., a + b instead of a+b )
• Determine what style to conform to 🙃
• Separate content into individual .tex files and use \include to collate into final book

Documentation

• Issue Template
• Pull request template
• Code of conduct
• Contributing guidelines
• Todo list on readme
• Update description for this project

Planned topics (Foundation)

• Numbers and their operations
• Percentages
• Algebraic expressions and formulae
  • Expansion and factorisation
  • Rational expressions
• Equations and inequalities
  • Substitution and elimination
  • Factorisation
  • Quadratic formula
• Exponential and logarithmic functions
• Set theory
  • Set notation
  • Union and intersection
  • Venn diagrams
• Summation
• Permutations and combinations

Planned topics (Statistics)

• Probability
  • Conditional probability
  • Bayes theorem

Good first issues

• Sample questions and worked solutions for each concept