Keith Ransom
Title
Cited by
Cited by
Year
How do people learn from negative evidence? Non-monotonic generalizations and sampling assumptions in inductive reasoning
W Voorspoels, DJ Navarro, A Perfors, K Ransom, G Storms
Cognitive psychology 81, 1-25, 2015
252015
The diversity effect in inductive reasoning depends on sampling assumptions
BK Hayes, DJ Navarro, RG Stephens, K Ransom, N Dilevski
Psychonomic bulletin & review 26 (3), 1043-1050, 2019
192019
Sample size, number of categories and sampling assumptions: Exploring some differences between categorization and generalization
AT Hendrickson, A Perfors, DJ Navarro, K Ransom
Cognitive Psychology 111, 80-102, 2019
192019
Leaping to conclusions: Why premise relevance affects argument strength
KJ Ransom, A Perfors, DJ Navarro
Cognitive science 40 (7), 1775-1796, 2016
172016
People ignore token frequency when deciding how widely to generalize
A Prefors, K Ransom, D Navarro
Proceedings of the Annual Meeting of the Cognitive Science Society 36 (36), 2014
142014
A cognitive analysis of deception without lying
K Ransom, W Voorspoels, A Perfors, D Navarro
Proceedings of the 39th Annual Conference of the Cognitive Science Society …, 2017
122017
Representational and sampling assumptions drive individual differences in single category generalisation
K Ransom, AT Hendrickson, A Perfors, DJ Navarro
Proceedings of the 40th annual conference of the cognitive science society, 2018
52018
Supporting software reuse within an integrated software development environment (position paper)
KJ Ransom, CD Marlin
ACM SIGSOFT Software Engineering Notes 20 (SI), 233-237, 1995
41995
Generating an implementation of a parallel programming language from a formal semantic definition
MJ Oudshoorn, CD Marlin, KJ Ransom
Department of Computer Science, The University of Adelaide, 1993
41993
Abstract data types: Converting from sequential to parallel
MJ Oudshoorn, KJ Ransom, CD Marlin
Australian Software Engineering Conference 1991: Engineering Safe Software …, 1991
31991
Do sequential lineups impair underlying discriminability?
M Kaesler, JC Dunn, K Ransom, C Semmler
Cognitive Research: Principles and Implications 5 (1), 1-21, 2020
12020
Where the truth lies: how sampling implications drive deception without lying
K Ransom, W Voorspoels, D Navarro, A Perfors
PsyArXiv, 2019
12019
Modelling systems that integrate programming language and environment mechanisms
KJ Ransom, CD Marlin
Proceedings 1995 Asia Pacific Software Engineering Conference, 274-281, 1995
11995
An Integrated Environment for the Development and Analysis of Hard Real-Time Systems
KJ Ransom, CD Marlin, W Zhao
IFAC Proceedings Volumes 24 (2), 27-32, 1991
11991
What interventions can decrease or increase belief polarisation in a population of rational agents?
P Howe, A Perfors, K Ransom
PsyArXiv, 2021
2021
What do our sampling assumptions affect: how we encode data or how we reason from it?
K Ransom, A Perfors, B Hayes, SC Desai
PsyArXiv, 2021
2021
Social meta-inference and the evidentiary value of consensus
KJ Ransom, A Perfors, RG Stephens
(forthcoming) Proceedings of 43rd Annual Conference of the Cognitive Science …, 2021
2021
Do sequential lineups impair discriminability?
M Kaesler, JC Dunn, K Ransom, C Semmler
PsyArXiv, 2020
2020
What lies behind the data? How sampling assumptions shape and are shaped by inductive inference
KJ Ransom
2019
Exploring the role that encoding and retrieval play in sampling effects.
K Ransom, A Perfors
CogSci, 946-952, 2019
2019
The system can't perform the operation now. Try again later.
Articles 1–20