BaleNorge on Nostr: Bayes' Theorem and show how it applies to everyday decision-making and belief ...
Bayes' Theorem and show how it applies to everyday decision-making and belief updating.
Let me explain how Bayes' Theorem helps us think better in everyday life:
1. **Starting Point (Prior)**: Begin with your initial belief about something. For example:
- "I think there's a 50% chance it will rain tomorrow"
- "I believe there's a 30% chance this restaurant is good"
2. **New Evidence**: You get new information that could change your belief:
- Weather: You see dark clouds gathering
- Restaurant: You see many positive reviews
3. **Update Your Belief**: Bayes' Theorem helps you rationally update your initial belief based on the new evidence.
Real-life examples:
1. **Job Interview**
- Prior: 40% chance of getting the job (based on typical odds)
- Evidence: Interview went very well
- Update: Increase your estimate to perhaps 60-70%
2. **Medical Diagnosis**
- Prior: 1% chance of having a condition (population average)
- Evidence: Positive test result (80% accurate)
- Update: New probability considering both pieces of information
3. **Relationship Red Flags**
- Prior: 80% chance relationship is healthy
- Evidence: Partner shows concerning behavior
- Update: Revise assessment based on new information
Key principles for using Bayesian thinking:
1. **Start with base rates**: Always consider how common something is in general
2. **Weigh evidence quality**: Strong evidence should change beliefs more than weak evidence
3. **Update gradually**: Change beliefs in steps as new information comes in
4. **Avoid extremes**: Be cautious about 0% or 100% certainty
5. **Consider alternative explanations**: Look for other possibilities
Let me explain how Bayes' Theorem helps us think better in everyday life:
1. **Starting Point (Prior)**: Begin with your initial belief about something. For example:
- "I think there's a 50% chance it will rain tomorrow"
- "I believe there's a 30% chance this restaurant is good"
2. **New Evidence**: You get new information that could change your belief:
- Weather: You see dark clouds gathering
- Restaurant: You see many positive reviews
3. **Update Your Belief**: Bayes' Theorem helps you rationally update your initial belief based on the new evidence.
Real-life examples:
1. **Job Interview**
- Prior: 40% chance of getting the job (based on typical odds)
- Evidence: Interview went very well
- Update: Increase your estimate to perhaps 60-70%
2. **Medical Diagnosis**
- Prior: 1% chance of having a condition (population average)
- Evidence: Positive test result (80% accurate)
- Update: New probability considering both pieces of information
3. **Relationship Red Flags**
- Prior: 80% chance relationship is healthy
- Evidence: Partner shows concerning behavior
- Update: Revise assessment based on new information
Key principles for using Bayesian thinking:
1. **Start with base rates**: Always consider how common something is in general
2. **Weigh evidence quality**: Strong evidence should change beliefs more than weak evidence
3. **Update gradually**: Change beliefs in steps as new information comes in
4. **Avoid extremes**: Be cautious about 0% or 100% certainty
5. **Consider alternative explanations**: Look for other possibilities