7 powerful lessons from the book The Book of Why1. Distinction between correlation and causation: This might seem obvious, but The Book of Why clearly demonstrates why correlation doesn't equal causation. We often misinterpret associations as causal relationships, leading to biased conclusions and ineffective solutions. The book provides frameworks like the "Ladder of Causation" to help us think critically about cause-and-effect relationships.2. The power of counterfactuals: To truly understand causation, we need to imagine alternative realities. Counterfactual thinking, asking "what if" questions, allows us to consider how things would have been different if a cause hadn't occurred. This is crucial for scientific discovery, policy-making, and even personal understanding.3. Causal inference beyond experiments: While randomized controlled trials (RCTs) are the gold standard for causal inference, they're not always feasible or ethical. The Book of Why introduces tools like the "do" operator and structural causal models that allow us to draw causal conclusions from observational data, paving the way for richer insights from real-world scenarios.4. The importance of causal models: Building strong causal models, like maps of cause-and-effect relationships, is crucial for understanding complex systems. These models help us predict the consequences of interventions, diagnose systemic problems, and design effective solutions in fields like medicine, economics, and even social policy.5. The limitations of "big data": The book cautions against blindly trusting massive datasets without considering causal models. Big data can reveal correlations, but it can also be misleading if we don't understand the underlying causal structure. Integrating causal frameworks is essential to extracting meaningful insights from the data deluge.6. The transformative power of causal understanding: Learning how to think causally has implications beyond science and research. It can empower us to make better decisions in our personal lives, understand societal issues more deeply, and ultimately build a more effective and just world.7. The future of causal science: The Book of Why is not just a retrospective; it also looks to the future of causal science. It highlights exciting advancements in artificial intelligence and machine learning that are being informed by causal principles, opening doors to previously unimaginable possibilities.BOOK: https://amzn.to/43dGlBP You can also get the AUDIO BOOK for FREE using the same link. Use the link to register for the AUDIO BOOK on Audible and start enjoying it.
7 powerful lessons from the book The Book of Why
1. Distinction between correlation and causation: This might seem obvious, but The Book of Why clearly demonstrates why correlation doesn't equal causation. We often misinterpret associations as causal relationships, leading to biased conclusions and ineffective solutions. The book provides frameworks like the "Ladder of Causation" to help us think critically about cause-and-effect relationships.
2. The power of counterfactuals: To truly understand causation, we need to imagine alternative realities. Counterfactual thinking, asking "what if" questions, allows us to consider how things would have been different if a cause hadn't occurred. This is crucial for scientific discovery, policy-making, and even personal understanding.
3. Causal inference beyond experiments: While randomized controlled trials (RCTs) are the gold standard for causal inference, they're not always feasible or ethical. The Book of Why introduces tools like the "do" operator and structural causal models that allow us to draw causal conclusions from observational data, paving the way for richer insights from real-world scenarios.
4. The importance of causal models: Building strong causal models, like maps of cause-and-effect relationships, is crucial for understanding complex systems. These models help us predict the consequences of interventions, diagnose systemic problems, and design effective solutions in fields like medicine, economics, and even social policy.
5. The limitations of "big data": The book cautions against blindly trusting massive datasets without considering causal models. Big data can reveal correlations, but it can also be misleading if we don't understand the underlying causal structure. Integrating causal frameworks is essential to extracting meaningful insights from the data deluge.
6. The transformative power of causal understanding: Learning how to think causally has implications beyond science and research. It can empower us to make better decisions in our personal lives, understand societal issues more deeply, and ultimately build a more effective and just world.
7. The future of causal science: The Book of Why is not just a retrospective; it also looks to the future of causal science. It highlights exciting advancements in artificial intelligence and machine learning that are being informed by causal principles, opening doors to previously unimaginable possibilities.
BOOK: https://amzn.to/43dGlBP
You can also get the AUDIO BOOK for FREE using the same link. Use the link to register for the AUDIO BOOK on Audible and start enjoying it.
Spectrum | 05.08.2008 | 04:30
New Drug for Prostate Cancer
Scientists are hailing a new drug to treat aggressive prostate cancer as a major breakthrough.
It’s called Abiraterone. And it could potentially treat up to 80% of patients with the deadliest form of the disease. The drug works by blocking the hormones which fuel the cancer. An advanced clinical trial is now underway and –- researchers hope – the treatment could be widely available in two or three years. From London Stephen Beard reports.
Our customers should take joy in our products and services.
Britain needs cheering up.
The UK - according to official statistics- suffers much higher levels of depression and anxiety than the restof Europe. The government wants to remedy the problem. It plans toprovide more psychological counselling on the state-run NationalHealth Service. But critics say that counselling is an ineffectivetreatment and that the government should address the causes ofdepression rather than trying to deal only with its symptoms. FromLondon Stephen Beard reports:
Quote from W. Edwards Deming:
Manage the cause, not the result.
菩薩重因 眾生重果 cause and effect (diagram)
cause━━ n. 原因, もと; 理由 ((to do)); 動機 ((for)); 【法】訴訟(の事由); 事件; 問題; 大義, 主義, 主張; 名分; 大目的; 運動.
symptom
━━ n. 徴候, しるし; 【医】症候.
adj.
aggressiveness ag·gres'sive·ness n.
菩薩重因 眾生重果 cause and effect (diagram)
cause━━ n. 原因, もと; 理由 ((to do)); 動機 ((for)); 【法】訴訟(の事由); 事件; 問題; 大義, 主義, 主張; 名分; 大目的; 運動.
symptom
━━ n. 徴候, しるし; 【医】症候.
aggressive
(ə-grĕs'ĭv)adj.
- Characterized by aggression: aggressive behavior.
- Inclined to behave in an actively hostile fashion: an aggressive regime.
- Assertive, bold, and energetic: an aggressive sales campaign.
- Of or relating to an investment or approach to investing that seeks above-average returns by taking above-average risks.
- Fast growing; tending to spread quickly and invade: an aggressive tumor.
- Characterized by or inclined toward vigorous or intensive medical treatment: an aggressive approach to treating the infection.
- Intense or harsh, as in color.
aggressiveness ag·gres'sive·ness n.
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