Cause-and-Effect Relationship
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A Cause-and-Effect Relationship is an asymmetric physical relationship between a causing event and a caused event.
References
2018
- (Pearl & Mackenzie, 2018) ⇒ Judea Pearl, and Dana Mackenzie. (2018). “The Book of Why: The New Science of Cause and Effect.” Hachette UK. ISBN:9780465097609
- QUOTE: … it is important to understand the achievements that causal inference has tallied thus far. We will explore the way that it has transformed the thinking of scientists in almost every data-informed discipline and how it is about to change our lives.
- The new science addresses seemingly straightforward questions like these:
- How effective is a given treatment in preventing a disease?
- Did the new tax law cause our sales to go up, or was it our advertising campaign?
- What is the health-care cost attributable to obesity?
- Can hiring records prove an employer is guilty of a policy of sex discrimination?
- I’m about to quit my job. Should I?
- These questions have in common a concern with cause-and-effect relationships, recognizable through words such as “preventing,” “cause,” “attributable to,” “policy,” and “should I.” Such words are common in everyday language, and our society constantly demands answers to such questions. Yet, until very recently, science gave us no means even to articulate, let alone answer, them. …
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/impact_evaluation Retrieved:2015-11-1.
- Impact evaluation assesses the changes that can be attributed to a particular intervention, such as a project, program or policy, both the intended ones, as well as ideally the unintended ones. … Impact evaluations seek to answer cause-and-effect questions. In other words, they look for the changes in outcome that are directly attributable to a program.
2007
- (Torbeck, 2007) ⇒ Lynn D. Torbeck. (2007). “Pharmaceutical and Medical Device Validation by Experimental Design." CRC Press. ISBN:1420055690
- QUOTE: Controlled multivariate experiments are the most logical, the most scientific, and the most efficient way that scientists know to collect data. … These observational tools cannot find and describe cause-and-effect relationships directly. The only way to find these relationships is to conduct a multivariate controlled-experiment.
In contrast to the observational approach, data collection in an controlled experiment is active; investigators take control of the environment and critical process parameters. By deliberate changes in key factors, the cause-and-effect relationships are forced to show themselves.
- QUOTE: Controlled multivariate experiments are the most logical, the most scientific, and the most efficient way that scientists know to collect data. … These observational tools cannot find and describe cause-and-effect relationships directly. The only way to find these relationships is to conduct a multivariate controlled-experiment.