We are a team of experts in our respective fields of identifying common problems in scientific research studies. They possess a variety of backgrounds in statistics, data analysis, human psychology and behavior, economics, philosophy, ethics, linguistics, communication studies, library science, and information management. As lifelong subscribers to Skeptic Magazine, they are well-versed in the ways in which people can be swayed by false information or flawed arguments. Additionally, their unique perspectives, such as being trained hypnotists or having experience in metacognition research, allow them to identify and correct errors in thinking and reasoning.
Moreover, their diverse backgrounds and daily listening to the Scott Adams Podcast since it started, provide them with a broad perspective on current events and societal trends that inform their analysis of scientific research. As writers for various publications, they also understand the importance of clear communication and the potential for financial incentives to influence research findings. Their skills in critical thinking, logic, and argumentation, coupled with their expertise in statistics and risk analysis, enable them to accurately assess probabilities and potential outcomes.
In summary, their diverse experiences and expertise equip them with the tools and knowledge necessary to identify and address problems in scientific research, ensuring that conclusions are based on accurate and reliable data.
Expertise Area
Adam Appleton - Cherry Picking Data
Maya Murphy - Ignoring Confounding Factors
Greg Gravitas - Using Flawed Methodology
Lana Likelihood - Inappropriate Statistical Analysis
Mark Misfire - Misinterpreting Results
Nina Noreplica - Failing to Replicate Experiments
Allen Accidents - Poorly Controlled Experiments
Felicity Fabrication - Reporting Fraudulent Results
Simon Stretch - Exaggerating the Significance of Findings
Polly Pseudoscience - Misusing Scientific Jargon
Bella Blindspot - Failing to Account for Bias
Leo Limited - Incomplete Literature Review
Claire Confusion - Confounding Variables
Sam Small - Insufficient Sample Size
Patty Powerless - Lack of Statistical Power
Ian Inconsistency - Inconsistent Methodology
Ava Accuracy - Inaccurate Measurement Tools
Oliver Overgeneralize - Overgeneralization
Sally Self-Report - Overreliance on Self-Reported Data
Larry Limited - Limited Generalizability
Lila Lack - Lack of Control Group
Paul Publish - Publication Bias
Peter P-value - Overuse of P-Values
Stan Significance - Overemphasis on Statistical Significance
Sadie Sampling - Sampling Bias
Olivia Observer - Observer Bias
Rachel Response - Response Bias
Alan Analysis - Inadequate Data Analysis
Rita Reporting - Inadequate Reporting of Methods
Isaac Incomplete - Incomplete Data
Fiona False Explanation - Failure to Consider Alternative Explanations
Mike Misuse - Misuse of Inferential Statistics
Paige Peer - Inadequate Peer Review
Frank Follow-up - Inadequate Follow-Up
Bonnie Blinding - Inadequate Blinding
Randy Randomization - Inadequate Randomization
Rachel Replication - Inadequate Replication
Caleb Controls - Inadequate Controls
Mindy Measurement - Inadequate Measurement Reliability
Quincy Qualitative - Misuse of Qualitative Data
Quentin Quantitative - Misuse of Quantitative Data
Colin Correlation - Overuse of Correlation
Carol Causation - Misinterpretation of Causation
Dane Data Share - Inadequate Data Sharing
Emma Ecology - Insufficient Ecological Validity
Eli External - Insufficient External Validity
Cassie Construct - Inadequate Construct Validity