Just Another Statistics Textbook
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About

  • Welcome
    • About
    • Installing R(Studio)
  • R Basics
    • Types of Scripts
    • R Fundamentals
    • R Logic
  • Statistics Foundations
    • Statistics Basics
    • Scientific Notation
    • Probability (R)
  • Describing Data
    • Central Tendency (R, Python, Excel, JASP)
    • Dispersion (R,Python, Excel, JASP)
  • Distributions
    • Binomial Distribution (R)
    • Normal Distribution
    • Skewness (R,Python)
    • Transforming Data (R)
  • Correlation
    • Correlations (R,Python)
    • Partial Correlations (R,Python)
  • Regressions
    • Simple regression (R)
    • Multiple Regressions (R)
  • General Linear Models
    • General Linear Models and Sum of Squares (R, Python)
    • T-Tests (R, Python incomplete)
    • One Way ANOVA (incomplete)
    • Repeated Measures ANOVAs
    • Mixed ANOVA (incomplete)
    • ANCOVA (incomplete)
  • Categorical
    • Contingency (R)
  • Item analyses
    • Cronbach’s Alpha (R,Python)
  • Multiple testing
    • Family-Wise Error (R)
    • False Discovery Rate(R)
    • FWER, FDR, Positive and Negative effects(R)
  • Permutations
    • Permutations (R)
    • Permutation vs. t tests (incomplete)
  • Excel tutorial
    • Formulas
    • If function
    • Count and countifs function
    • Sum and SumIf
    • Averageifs
    • Anchoring
  • Test yourself
    • All questions
    • Question Maker

On this page

  • Contributions (in alphabetical order)

About

Developed at the University of Reading School of Psychology and Clinical Language Sciences. This is not developed by the same team as JASP (although JASP is great).

Course Overview

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Gray means that the page doesn’t yet have separation of different levels of understanding

Orange means that the page is started

In this website you can choose to expand or shrink the page to match the level of understanding you want.

  • If you do not expand any (green) subsections then you will only see the most superficial level of description about the statistics. If you expand the green subsections you will get details that are required to complete the tests, but perhaps not all the explanations for why the statistics work.
An example of a green subsection
  • If you expand the blue subsections you will also see some explanations that will give you a more complete understanding. If you are completing MSc-level statistics you would be expected to understand all the blue subsections.
An example of a blue subsection
  • Red subsections will go deeper than what is expected at MSc level, such as testing higher level concepts.
An example of a red subsection

This textbook is under-development (https://github.com/Reading-Psych/jast), and is aimed at students in the school of Psychology and Clinical Language Sciences. The aim will be to focus on statistics taught in MSc students in Reading using the following software:

  • Microsoft Excel (in the future)
  • R (open-source)
  • Python (in development)

Do make use of the search-bar in the top-right to find any content within the website.

Contributions (in alphabetical order)

Surname First Name Contribution
Biagi Nico Architect, Author
Brady Dan Architect, Author
Goh Vera Suggestions
Haffey Anthony Architect, Author
Mathews Imogen Author
Pritchard Katherine Suggestions
Sahni Angad Contributor
  • Architects have managed the formatting of this website/textbook
  • Authors have written (sub)sections
  • Contributors have contributed text for a subsection
  • Suggestions are requests for elaborations and clarifications