Danielle Navarro
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Learning Statistics with jamovi Open
Based on Danielle Navarro’s widely acclaimed and prize-winning book Learning Statistics with R, this elegantly designed textbook offers undergraduate students a thorough and accessible introduction to jamovi, as well as how to get to grips…
12. Correlation and linear regression Open
This chapter delves into correlation and linear regression, foundational techniques in statistical analysis for exploring relationships between continuous predictors and outcomes. Beginning with the concept of correlations, the chapter exa…
16. Bayesian statistics Open
Chapter 16 introduces Bayesian statistics as an alternative to the frequentist perspective commonly used in psychology and other scientific disciplines. The chapter begins by critiquing the dominance of frequentist methods, noting their li…
14. Factorial ANOVA Open
Chapter 14 explores the extension of ANOVA to factorial designs, allowing for the analysis of data influenced by multiple categorical predictor variables. This chapter builds on previous concepts introduced in simpler ANOVA and regression …
13. Comparing several means (one-way ANOVA) Open
This chapter delves into the foundational principles and applications of one-way ANOVA (Analysis of Variance), a pivotal statistical tool introduced by Sir Ronald Fisher in the early 20th century. Despite its name suggesting a focus on var…
2. A brief introduction to research design Open
This chapter introduces the foundational principles of research design, emphasizing the interplay between data collection and analysis. It provides an overview of the key concepts in operationalizing theoretical constructs into measurable …
5. Drawing graphs Open
This chapter explores the fundamental role of data visualisation in the analytical process, highlighting its dual purposes: as a tool for presenting information in an accessible and visually compelling manner, and as an aid to enhance unde…
9. Hypothesis testing Open
This chapter explores hypothesis testing, the second foundational concept in inferential statistics, after estimation. At its core, hypothesis testing involves determining whether the data support a specific theory about the world. Despite…
4. Descriptive statistics Open
In this chapter, we delve into the fundamentals of descriptive statistics, a crucial step in data analysis that involves summarising datasets into comprehensible and concise forms. The chapter begins by exploring the rationale behind descr…
8. Estimating unknown quantities from a sample Open
This chapter delves into the distinction between descriptive and inferential statistics, focusing on the latter’s aim of deriving knowledge about unknown population parameters from observed data. It introduces estimation theory, the first …
11. Comparing two means Open
In this chapter, we delve into the statistical techniques used to compare the means of two groups, particularly when the outcome variable is on an interval or ratio scale, and the predictor variable is binary. Such scenarios are prevalent …
15. Factor Analysis Open
This chapter provides an in-depth exploration of Factor Analysis (FA), a statistical approach used to examine the relationships among multiple variables to uncover underlying latent factors. Latent factors represent unobservable constructs…
Epilogue Open
This chapter serves as an epilogue, exploring the vast universe of statistics that lies beyond the foundational concepts covered in the book. Highlighting the limitations of introductory courses, it emphasises that mastering basic tools su…
7. Introduction to probability Open
This chapter serves as a foundational exploration of probability, bridging the gap between descriptive statistics and the deeper domain of inferential statistics. Beginning with a reflection on the interplay between probability and statist…
10. Categorical data analysis Open
This chapter introduces the foundational concepts and methods of categorical data analysis, focusing on the chi-square (χ²) tests. It begins by exploring the theory and application of the χ² goodness-of-fit test, a statistical tool used to…
3. Getting started with jamovi Open
Chapter 3 of the book introduces readers to the statistical software jamovi, guiding them through the initial steps of downloading, installing, and familiarising themselves with its interface. The chapter emphasises the advantages of using…
1. Why do we learn statistics Open
This chapter introduces the critical role of statistics in psychological and social sciences, emphasizing its importance despite students’ frequent apprehension toward the subject. Statistics is central to science because it serves as a sa…
6. Pragmatic matters Open
This chapter offers a pragmatic exploration of data manipulation, addressing the often-messy realities of working with real-world datasets. It introduces foundational techniques for managing and preparing data, such as tabulating and cross…
Confidence regulates feedback processing during human probabilistic learning. Open
Uncertainty presents a key challenge when learning how best to act to attain a desired outcome. People can report uncertainty in the form of confidence judgments, but how such judgments contribute to learning and subsequent decisions remai…
View article: Bayes Factors for Mixed Models: A Discussion
Bayes Factors for Mixed Models: A Discussion Open
van Doorn et al. (2021) outlined various questions that arise when conducting Bayesian model comparison for mixed effects models. Seven response articles offered their own perspective on the preferred setup for mixed model comparison, on t…
Advancing Innovation and Access to Medicines Open
When the Sustainable Development Goals were agreed in 2015, Goal 3 called upon the world to "ensure healthy lives and promote well-being for all." Health technologies are not ordinary consumer goods but rather essential goods, just like fo…
The unbearable limitations of solo science: Team science as a path for more rigorous and relevant research Open
Both early social psychologists and the modern, interdisciplinary scientific community have advocated for diverse team science. We echo this call and describe three common pitfalls of solo science illustrated by the target article. We disc…
Statistics in the Service of Science: Don't let the Tail Wag the Dog Open
Statistical modeling is generally meant to describe patterns in data in service of the broader scientific goal of developing theories to explain those patterns. Statistical models support meaningful inferences when models are built so as t…
The Unbearable Limitations of Solo Science: Team Science as a Path for more Rigorous and Relevant Research Open
Both early social psychologists and the modern, interdisciplinary scientific community have advocated for diverse team science. We echo this call and describe three common pitfalls of solo science illustrated by the target article. We disc…
The case for formal methodology in scientific reform Open
Current attempts at methodological reform in sciences come in response to an overall lack of rigor in methodological and scientific practices in experimental sciences. However, most methodological reform attempts suffer from similar mistak…