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# Synergy Science

What is Synergistic Data Science: 3 Blogs and a Glossary. Sponsored by Synergy Data Science

## Sitemaps

- [XML Sitemap](https://synergy.science/sitemap.xml): Contains all public & indexable URLs for this website.

## Posts

- [AI and Productivity in Software Development-Thoughts and Comments](https://synergy.science/ai-and-productivity-in-software-development-thoughts-and-comments/) - In my first post for the new synergy.science blog, I concentrate on a very recent article about the salient issue in an AI-driven labor and occupational restructuring that may be imminent in software development. This article is available for a no-charge download. Here are some details: “The Effects of Generative AI on High Skilled Work:
- [7 Synergistic Data Science Strategies for Businesses Large or Small](https://synergy.science/7-synergistic-data-science-strategies-for-businesses-large-or-small/)
- [12 Ways Synergistic Data Science Models Can Help Your Business](https://synergy.science/12-ways-synergistic-data-science-models-can-help-your-business/) - Dr. Gordy Fairchild & Poe AI (assistant) Data science models in business are often employed to address a variety of business metrics and objectives. Synergistic data science beefs up the advantages below by using numerous methods to generate more powerful insights. Some common business metrics and objectives that data science models can target include: 1.
- [12 Fundamental Ways Synergistic Data Science Models Can Help Your Business](https://synergy.science/home-fun-2/) - Dr. Gordy Fairchild & Poe AI (assistant) Data science models in business are often employed to address a variety of business metrics and objectives. Synergistic data science beefs up the advantages below by using numerous methods to generate more powerful insights. Some common business metrics and objectives that data science models can target include: 1.
- [Data Science in a Big Data World: Analytics Life Cycle & BI-Chasm](https://synergy.science/home-fun/)
- [What’s in a fundamental definition: AI, ML, Data Science, Statistics, Analytics, and Econometrics?](https://synergy.science/home-fun-3/) - By Dr. Dean G. "Gordy" Fairchild (CEO, Synergy Data Science), poe.com AI (Assistant) While there is some overlap among these terms, they represent often too-distinct fields and approaches. Here’s an overview of the differences among the terms “data science,” “artificial intelligence” (AI), analytics, statistics, “machine learning,” and econometrics. It should be noted that to some
- [What’s in a definition: AI, ML, Data Science, Statistics, Analytics, and Econometrics?](https://synergy.science/whats-in-a-definition-ai-ml-data-science-statistics-and-analytics-and-econometrics/) - By Dr. Dean G. "Gordy" Fairchild (CEO, Synergy Data Science), poe.com AI (Assistant) While there is some overlap among these terms, they represent often too-distinct fields and approaches. Here’s an overview of the differences among the terms “data science,” “artificial intelligence” (AI), analytics, statistics, “machine learning,” and econometrics. It should be noted that to some
- [Sampling: New-School Approaches & Old-School Approaches](https://synergy.science/sampling-new-school-approaches-compared-with-old-school-approaches/) - DRAFT UNDER LIVE CONSTRUCTION By Dr. Dean G. "Gordy" Fairchild (CEO, Synergy Data Science), poe.com AI (Assistant) New-School Sampling In new-school problems, practitioners typically use all the available data to perform many kinds of analyses even if there are billions of observations. The standard approach is to draw a training sample from which a model
- [A Data Scientist’s Look at Synergistic Data Science](https://synergy.science/what-do-data-scientists-gain-from-using-synergistic-data-science/) - Dr. Gordy Fairchild, CEO SynergyData.science & queries from Poe AI. Synergistic data science refers to the integration and collaboration of different disciplines, industries, and techniques within the field of data science to achieve enhanced results and insights. It involves combining various methodologies, tools, and expertise from domains such as economics, statistics, machine learning, computer science,
- [Are outliers bad news for data scientists? Should they be thrown out of modeling datasets or models themselves?](https://synergy.science/outliers/) - By Dr. Dean G. "Gordy" Fairchild (CEO, Synergy Data Science), poe.com AI (Assistant), poe.com Data-Scientist-GPT3, Univ of California Berkely Statistics Glossary, Data Camp Data Science Glossary The answer to both questions depends on old-school vs. new-school viewpoint as well as the context of the problem and what type of outlier is being described. One thing
- [Data Reliability and Validity, Redux](https://synergy.science/data-reliability-and-validity-redux/) - August 1 2023 By Dr. Bill Luker (Synergy Data Science) Here is a recent post, from the vast LinkedIn commentariat, that raises the often neglected issue of reliability and analytic validity (R&V) in survey data. Since survey data constitutes such a huge proportion of all data collected by business and academic research scientists, it’s important.
- [Business Importance of Synergistic Data Science](https://synergy.science/importance-of-synergistic-data-science/) - By Dr. Dean G. "Gordy" Fairchild (CEO, Synergy Data Science), poe.com AI (Assistant) Synergistic data science is important to businesses for several reasons: Business Results. Understanding that your data is an important asset that can produce enormous returns. Enhanced Decision-Making: By integrating diverse techniques and expertise, synergistic data science enables businesses to make more informed
- [Role Played in Science by Synergistic Data Science](https://synergy.science/role-played-in-science-by-synergistic-data-science/) - By Dr. Dean G. "Gordy" Fairchild (CEO, Synergy Data Science), poe.com AI (Assistant) Synergistic data science plays a valuable role in scientific disciplines by aiding in the testing of hypotheses and the explanation of phenomena (OS). Synergistic data science helps science by creating answers to questions that the researcher did not ask---but should have (NS).
- [What’s in a definition: AI, ML, Data Science, Statistics, Analytics, and Econometrics?](https://synergy.science/data-scientist-science-community-whats-in-a-definition-ai-ml-data-science-statistics-analytics-and-econometrics/) - Dr. Gordy Fairchild & Poe AI. While there is some overlap among these terms, they represent distinct fields and approaches. Here’s an overview of the differences among the terms “data science,” “artificial intelligence” (AI), analytics, statistics, “machine learning,” and econometrics. It should be noted that to some practitioners AI includes all the other terms as
- [Model Management is a Team Activity](https://synergy.science/model-management-is-a-team-activity/) - By Keith Schleicher, Data Science, Analytics, and AI/ML Leader While there is a wide array of personalities within the realm of Predictive Analytics/Data Science professionals, one would not use “extrovert” as a first word to describe a typical member of this profession. Most of us went into this line of work because we love to
- [What is Multicollinearity? Why Does it Matter? When can it be Ignored? What Models are Affected? How is it Diagnosed and Corrected?](https://synergy.science/the-myths-of-multicollinearity/) - Dr. Gordy Fairchild (CEO of Synergy Data Science) Misinformation about multicollinearity is commonplace. In short, there is disagreement among practitioners about many facets of multicollinearity. Both new-school and old-school data scientists often handle it in different ways. Inexperienced new-school practitioners who have been trained quickly in a data science boot camp typically do not have
- [How do you set the optimal cut-off (probability threshold) for classifiers without blindly using the default of 0.5?](https://synergy.science/how-do-you-set-the-optimal-cut-off-probability-threshold-for-classifiers-without-blindly-using-the-default-value-of-0-5/) - Setting probability thresholds in classification models depends on the specific requirements of your problem and the trade-offs you are willing to make between precision and recall (aka sensitivity or the True Positive Rate. In binary and categorical classification, the model typically outputs a probability score for each class, and a threshold is applied to determine

## Pages

- [WELCOME TO SYNERGY.SCIENCE: What is Synergistic Data Science?](https://synergy.science/) - Our 3 Blogs and Data Science New-Shool vs. Old-School Have Answers, Questions, and Discussion: 1) For Businesses: A strategy to translate your valuable data into profitable insights & revenue-generating tactics, proactive forecasts, and real-time financial reporting. Synergistic data science uses methods from across sciences and industries so you gain new customers, boost loyal customer spend,
- [Contact](https://synergy.science/contact/) - Use this contact form for any reason to contact us. Please send an e-mail with a subject line mentioning SYNERGY.SCIENCE if you are interested in contrubuting a post, editing posts, or any questions/comments about the site we will be in touch by email.
- [New-School Vs Old-School Glossary](https://synergy.science/new-school-vs-old-school-glossary/) - A KEY TO THE DATA SCIENCE "TOWER OF BABEL" Terminology---sometimes referred to as “nomenclature”—is important in every field. In data science, New School (NS) and Old School (OS) nomenclature may be identical, sometimes defined in only one school, but often differs between the OS & NS even for the same word. We help mediate this
- [What is Synergistic Data Science for Data Scientists?](https://synergy.science/data-scientist/) - By Dr. Dean G. "Gordy" Fairchild (CEO, Synergy Data Science), poe.com AI (Assistant) Synergistic data science refers to the integration and collaboration of different disciplines, industries, and techniques within the field of data science to achieve enhanced results and insights. It involves combining various methodologies, tools, and expertise from domains such as economics, statistics, machine
- [How Does Synergistic Data Science Benefit Analyses Within the Scientific Community?](https://synergy.science/science-community/) - OUTLINE: 1. Cross-Disciplinary 2. Cross-Paradigm 3. Cross-Method 4. Yields (positive synergy only): a. 2+2 > 4 b. 3×3 > 9 No mistake in the math. The whole is greater than the sum of its parts. 5. Holistic Power of Synergy. The whole is greater than the sum of its parts. 6. Not an “Answer” but
- [What Does Synergistic Data Science Mean for Business?](https://synergy.science/business/) - It’s about Stakeholder delight. Businesses have stakeholders each of whom can benefit from data science applications. In the case of small and mid-sized businesses, there may be fewer stakeholders but always some will be delighted by synergistic data science. CUSTOMERS, PROSPECTS & WIN-BACKS EMPLOYEES, HUMAN RESOURCES, AND FRONT-LINE MONITORING OWNERS & SHAREHOLDERS VENDORS & STRATEGIC

## Categories

- [Business](https://synergy.science/category/business/)
- [Data Scientist](https://synergy.science/category/data-scientist/)
- [new school vs old school](https://synergy.science/category/new-school-vs-old-school/)
- [Science Community](https://synergy.science/category/science-community/)
- [home](https://synergy.science/category/home/)

## Tags

- [Fundamental](https://synergy.science/tag/fundamental/)