Join us as Dr. Allen Downey, renowned author and professor, shares insights from his upcoming book 'Probably Overthinking It,' breaking down underused techniques like Survival Analysis, explaining common paradoxes, and discussing the dynamic Overton Window.

This episode is brought to you by the Zerve data science dev environment (https://zerve.ai), by Modelbit (https://modelbit.com), for deploying models in seconds, and by Grafbase (https://grafbase.com), the unified data layer. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• Why interpreting data is not always easy [06:21]
• What is Survival Analysis [15:32]
• Preston's Paradox [22:09]
• Are you Normal? [36:52]
• How to better prepare for rare “Black Swan” events [42:48]
• What is an Overton Window? [53:06]
• What is the base rate fallacy? [1:23:31]
• How to protect yourself from biased samples [1:33:39]
• Simpson’s Paradox [1:42:43]

Additional materials: www.superdatascience.com/715

The Super Data Science Podcast: Machine Learning | AI | Success

715: Make Better Decisions with Data, with Dr. Allen Downey

On-Demand College Sports Communicators Webinar

Using web and social media analytics to make data-driven decisions

The presenters discussed the importance for athletic communicators and creatives to gather data and insights in real time as it pertains to your web and social media content. They discussed how social media data mining gives you key insights into your audience so you can learn what kind of content they like, when they want to see it, and where they spend their time online.

Panelists
• Sam Knehans –  Sun Belt Conference Senior Associate Commissioner, Chief Communications and Branding Officer 
• Chris Jones –  New York Red Bulls Manager, Digital and Social Content
• Phylicia Short –Queens University (Charlotte) Assistant Athletic Director for Communications / Athletics Diversity & Inclusion Designee
• Moderator: Eliza Kravitz, Georgetown University Assistant Director of Athletic Communications

While many platforms have their own built-in insights, using a social media analytics tool or tools can help you collect all of that data in a single, easy-to-use dashboard; those tools were discussed. Also:

Collecting the Data
What social media data you should be tracking, with tips for smart social media data collection
How to collaborate with on-campus colleagues to deliver data/analytics to support your brand messaging and brand content
Phylicia Short (Queens): Led athletic department effort to partner with the Queens business school as they moved to NCAA Division I to create their analytics strategies; suggested schools work with their campus constituents (business school, analytics, masters programs) to assist in collection of data, and to use tools like Sprout Social to collect the data.
 
Analyzing the Data and Making the Case
How to use analytics to inform and build your social media strategies to help your brand(s) gauge key metrics like reach, followers, engagement, clicks and conversations
Sam Knehans: Ask: To establish your social analytics strategy, ask: What are we using our time on? What content moves the needle? Review of tools the Sun Belt Conference uses. Review your analytics each semester.

Chris Jones - Making decisions based on the data, always asking: Why do we think it worked/didn’t work? How can we learn and improve? Review and refine your strategy often.


Other Resources 

August 2023 - Rival IQ's Higher Education Social Media Engagement Report for all NCAA Division I and Division I Universities and Colleges: https://www.rivaliq.com/blog/higher-ed-social-media-engagement-report/

March 2023 - MIT Sloan Sports Analytics Conference Session: Social Media and Sports: How Consumption and Fanhood is Changing via https://www.youtube.com/watch?v=qOw5vJ_vy6s

Webinar: Using web and social media analytics to make data-driven decisions

Jerry Yurchisin from Gurobi joins Jon Krohn to break down mathematical optimization, showing why it often outshines machine learning for real-world challenges. Find out how innovations like NVIDIA’s latest CPUs are speeding up solutions to problems like the Traveling Salesman in seconds.

Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

In this episode you will learn:
• The Burrito Optimization Game and mathematical optimization use cases [03:36]
• Key differences between machine learning and mathematical optimization [05:45]
• How mathematical optimization is ideal for real-world constraints [13:50]
• Gurobi’s APIs and the ease of integrating them [21:33]
• How LLMs like GPT-4 can help with optimization problems [39:39]
• Why integer variables are so complex to model [01:02:37]
• NP-hard problems [01:11:01]
• The history of optimization and its early applications [01:26:23]

Additional materials: www.superdatascience.com/813

813: Solving Business Problems Optimally with Data, with Jerry Yurchisin

"In This Episode"
This episode of Katalysts by Katalyze AI dives deep into the world of artificial intelligence, featuring Paul Kim’s insights on its transformative potential across industries. With over 30 years of experience in Washington DC, Paul Kim advises patient advocates, global life science leaders, and innovative emerging companies on FDA and public health policy- developing legislative and policy strategies for regulatory reforms, drafting and enacting Federal legislation, and securing funding or creating effective P3s.

The conversation explores pivotal breakthroughs, ethical dilemmas, and the critical role of transparency and regulation in shaping the future of AI. From the practical applications of AI in fields like healthcare to concerns about job displacement and biases in systems, the discussion provides a balanced view of both the opportunities and challenges AI presents.

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Experience how Katalyze AI’s platform can transform your operations by enhancing yield, improving traceability, and reducing cycle times across your biopharma processes.

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"Book Your Free Demo Now" 
https://katalyzeai.com/contactus


Unlocking AI's Potential: Paul Kim’s Insights

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

College Sports Communicators is the premier professional and educational association for strategic, creative and digital communicators across intercollegiate athletics in the U.S. and Canada. Known as College Sports Information Directors of America (CoSIDA) for its first 65 years (1957-2022), the organization adopted a new name and associated visual identity in 2022-23.

Our new brand identity is a major step in a larger strategic plan to define the association’s evolution and expansion. It is designed to represent our brand promise –- connect and support all communicators in college sports through advocacy, leadership, education, recognition and collaboration.

New tracks tagged #Data Driven Decisions