Don't just trust the numbers—interrogate them. Learn to identify weak statistical claims and misleading data.
P-Values
Significance tests
Sample Size
Power analysis
Bias Detection
Spot problems
Critical Reading
Media literacy
You are a statistical skepticism engine. Your job is to analyze headline claims and find the fatal flaw in the data.
Stats Skeptic is a data literacy game that builds your ability to critically evaluate statistical claims. In an age of data-driven arguments, distinguishing good statistics from misleading ones is essential.
The game presents statistical claims for you to evaluate. You develop the critical thinking skills to spot flawed reasoning, misleading graphs, and unsupported conclusions.
The game covers statistical reasoning:
Fallacy Types: • Sampling Bias: Unrepresentative or small samples • Misleading Visualizations: Distorted graphs and charts • Correlation Issues: Confusing correlation with causation • Selection Bias: Survivorship bias and cherry-picking • Statistical Manipulation: p-hacking, leading questions
Real Examples: Claims from media, marketing, and research.
Read a statistical claim or data-based argument.
Look at how data was collected and presented.
Identify statistical fallacies or misleading presentations.
Determine if the conclusion is supported by the data.
Stats Skeptic develops analytical abilities:
Critical Evaluation: Questioning claims before accepting.
Data Interpretation: Reading statistics accurately.
Logical Analysis: Spotting reasoning flaws.
Source Assessment: Evaluating data quality.
Conclusion Validation: Checking if data supports claims.
Statistical reasoning helps data-heavy exams:
GMAT Data Interpretation: Evaluating data-based arguments.
CAT DI/LR: Interpreting data and finding conclusions.
Research Methods: Understanding study validity.
Critical Reasoning: Spotting flawed arguments.
Stats Skeptic benefits information consumers:
• MBA Aspirants: Build data literacy for business • Researchers: Evaluate study quality critically • Journalists: Assess statistical claims accurately • Managers: Make data-driven decisions wisely • Everyone: Navigate information age effectively
This game applies data literacy research:
Statistical Misconceptions: Common errors can be corrected.
Critical Thinking: Skepticism improves with practice.
Media Literacy: Data literacy is a core media skill.
Decision Quality: Understanding statistics improves choices.
Always ask: how was this data collected and by whom?
Check sample sizes - small samples mean unreliable results
Look at absolute numbers, not just percentages
Consider what data might be missing or hidden
Be especially skeptical of claims that seem too perfect
