The error bar representation of a confidence interval is the most ubiquitous display of uncertainty in statistical analysis. However, despite this, error bars are poorly understood even by seasoned scientists and researchers across disciplines. The root of this misunderstanding is not certain, but researchers have posited several hypotheses ranging from the structure of the display itself, to how it is presented in the classroom. Studies have thus far been either incomplete or inconclusive, leading some to call for the elimination of the use of error bars entirely. However, research into statistics education (suggesting the error bar representation may not even be taught in contemporary classrooms) demonstrates that a lack of exposure in an...
The mechanisms that enable humans to evaluate their confidence across a range of different decisions...
Although calibration has been widely studied, questions remain about how best to capture confidence ...
Learning in a stochastic environment consists of estimating a model from a limited amount of noisy d...
The frequent misinterpretation of the nature of confidence intervals by students has been well docum...
Miller and Ulrich (2015) critique our claim (Hoekstra et al., Psychonomic Bulletin & Review, 21(5), ...
The aim of this study was to gain knowledge of students ’ beliefs and difficulties in understanding ...
Miller and Ulrich (2015) critique our claim (Hoekstra et al., Psychonomic Bulletin & Review, 21(...
The following files accompany this module: 11_Examples.xlsx 11_Exercises.xlsx 11_GallupMarijuana.x...
This paper describes responses first-year university students gave to a survey asking them about the...
Hoekstra et al. (Psychonomic Bulletin & Review, 2014, 21:1157–1164) surveyed the interpretation of c...
A confidence interval (CI) is an interval estimate of a population parameter. Instead of estimating ...
Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have b...
Confidence in a perceptual decision is a judgment about the quality of the sensory evidence. The qua...
Confidence intervals are presented in various scientific fields and are used to justify claims,altho...
Introduction: Reporting confidence intervals in scientific articles is important and relevant for ev...
The mechanisms that enable humans to evaluate their confidence across a range of different decisions...
Although calibration has been widely studied, questions remain about how best to capture confidence ...
Learning in a stochastic environment consists of estimating a model from a limited amount of noisy d...
The frequent misinterpretation of the nature of confidence intervals by students has been well docum...
Miller and Ulrich (2015) critique our claim (Hoekstra et al., Psychonomic Bulletin & Review, 21(5), ...
The aim of this study was to gain knowledge of students ’ beliefs and difficulties in understanding ...
Miller and Ulrich (2015) critique our claim (Hoekstra et al., Psychonomic Bulletin & Review, 21(...
The following files accompany this module: 11_Examples.xlsx 11_Exercises.xlsx 11_GallupMarijuana.x...
This paper describes responses first-year university students gave to a survey asking them about the...
Hoekstra et al. (Psychonomic Bulletin & Review, 2014, 21:1157–1164) surveyed the interpretation of c...
A confidence interval (CI) is an interval estimate of a population parameter. Instead of estimating ...
Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have b...
Confidence in a perceptual decision is a judgment about the quality of the sensory evidence. The qua...
Confidence intervals are presented in various scientific fields and are used to justify claims,altho...
Introduction: Reporting confidence intervals in scientific articles is important and relevant for ev...
The mechanisms that enable humans to evaluate their confidence across a range of different decisions...
Although calibration has been widely studied, questions remain about how best to capture confidence ...
Learning in a stochastic environment consists of estimating a model from a limited amount of noisy d...