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Garbage In, Garbage Out

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In other words, cost-benefit analysis is only as good as the numbers you put into it. In computer science, there is a model describing this phenomenon: garbage in, garbage out. If your estimates of costs and benefits are highly inaccurate, your timelines don't line up, or your discount rate is poorly reasoned (garbage in), then your net result will be similarly flawed (garbage out).

From

Chapter:

Decisions, Decisions

Section:

Weighing The Costs And Benefits

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Anecdotal evidence
Correlation Does Not Imply Causation
Confounding Factor
Hypothesis
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Randomized Controlled Experiment
A/B Testing
Observer-Expectancy Bias
Placebo Effect
Proxy
Selection Bias
Survivorship Bias
Response Bias
Law Of Large Numbers
Gambler's Fallacy
Clustering Illusion
Regression To The Mean
Median
Mode
Variance
Standard Deviation
Normal Distribution
Probability Distribution
Central Limit Theorem
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Power
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Statistical Significance
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Replication Crisis
Data Dredging
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Systematic Review
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Maslow's Hammer
Cost-Benefit Analysis
Inflation
Sensitivity Analysis
Garbage In, Garbage Out
Decision Tree
Expected Value
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Utilitarianism
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Systems Thinking
Chatelier's principle
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Local Optimum
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Unknown Unknowns
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Counterfactual Thinking
Lateral Thinking
Groupthink
Bandwagon Effect
Divergent Thinking
Convergent Thinking
Crowdsource
Prediction Market
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