Statistics for Psychology A Beginner′s Guide 2nd Edition By Roger Watt, Elizabeth Collins
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Statistics for Psychology A Beginner′s Guide 2nd Edition By Roger Watt, Elizabeth Collins

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359
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About this ebook
The Statistics for Psychology: A Beginner's Guide (2nd Edition) by Roger Watt and Elizabeth Collins provides a highly visual, software-agnostic approach to foundational statistics in psychological research. [1, 2]
The primary core topics covered across its chapters include: [1, 2]
Foundations & The Research Cycle
  • The Research Cycle: Breaking down ideas, hypothesis formulation, design, evidence gathering, data analysis, inference, and the presentation of results. [1]
  • Variables & Measurement: Exploring interval, ordinal, and categorical data, alongside classification frameworks like between-participants, within-participants, observational, experimental, and latent variables. [1, 2]
  • Measurement Accuracy & Research Design: Identifying sampling pitfalls, design strategies, and mitigating data errors. [1]
Descriptive Statistics & Main Statistical Principles
  • Relationships & Effect Sizes: Quantifying variable connections and measuring how meaningful an effect is.
  • Variability & Uncertainty: Structuring descriptions of variability and sampling error.
  • Null Hypothesis Significance Testing (NHST): Traditional inferential statistical logic and its limitations.
  • Alternatives to NHST: Concepts surrounding Bayesian statistics and likelihood approaches. [1]
Advanced Modeling & Complex Designs
  • General Linear Models (GLM): Using linear modeling strategies for complex analysis.
  • ANOVA & Multi-Variable Designs: Evaluating main effects, interactions, and covariation when testing multiple independent variables.
  • Model Comparisons & Advanced Paths: Structural topics including mediation, path models, and model comparison criteria.
  • Replication & Meta-Analysis: Contemporary tools for synthesizing research findings and assessing scientific reliability. [1]
New Features in the 2nd Edition
  • Responsible Research Practices: Integrated content discussing open science, research ethics, and transparent modeling.
  • Communicating with Critical Audiences: A dedicated chapter guiding students on how to formally present their statistical evidence. [1, 2]

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Topics

Advanced Modeling & Complex Designs Alternatives to NHST ANOVA & Multi-Variable Designs Communicating with Critical Audiences Descriptive Statistics & Main Statistical Principles Foundations & The Research Cycle General Linear Models GLM Measurement Accuracy & Research Design Model Comparisons & Advanced Paths Null Hypothesis Significance Testing NHST Relationships & Effect Sizes Replication & Meta-Analysis Responsible Research Practices The Research Cycle Variability & Uncertainty Variables & Measurement
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