Shows
The Effective Statistician - in association with PSIHow AI Can Help Us with Our Day-to-day Work! Experiences with CopilotInterview with Paolo Eusebi
Key Points:
AI in Daily Work
GitHub Copilot
Code Suggestions
Learning Tool
R Studio Integration
Productivity Boost
Data Privacy
Future of AI
As AI continues to revolutionize the way we work, tools like GitHub Copilot offer incredible opportunities to enhance productivity, simplify complex tasks, and accelerate learning. In this episode, Paolo and I dive into the practical applications of Copilot in our day-to-day work, sharing insights that can benefit statisticians and data scientists alike. Don’t miss out on this valuable discussion!
Tune in to the episode now, and if you fi...2024-09-1621 min
The Effective Data ScientistAs a Statistician - Do You Take the Back Seat or Do You Drive Yourself? (Episode 24)Discussion with Alexander Schacht and Benjamin Piske
how it relates to your goals,
what it takes to think strategically,
which role innovation has here,
what practical steps to take to drive teams forward,
which knowledge to acquire to lead teams successfully,
how this relates to influencing,
and how your attitude will play a big role in this.
2024-01-2521 minThe Effective Data ScientistOn Building Your Own Company (Episode 23)Interview with Shafi Chowdhury
In this episode, we’ll cover an amazing story by one of the best programmers and mentors I ever worked with - Shafi Chowdhury (www.shaficonsultancy.com).
We’ll explore how it changed from being a freelance programmer only to building his company on the side. He had a great vision in mind, that drove him forward.
You’ll also hear about his approach to teaching and mentoring – or in general helping people do their job better. His abundance mindset inspires me a lot. Shafi explains, why and how he made his own job redundant in his own...2024-01-1144 minThe Effective Data ScientistCluster Analysis (Episode 22)Discussion with Alexander Schacht and Paolo Eusebi
000000E2 000000E0 00002DDD 00002879 000099FA 0000A568 00007FBA 00006CBA 00004C39 0000A2242023-12-2932 minThe Effective Data ScientistDimension Reduction with PCA (Episode 21)Discussion with Alexander Schacht and Paolo Eusebi
0000016B 0000015F 000045CA 00003CF4 0013891F 000E045E 00007FBA 00006E82 00004C39 001366D62023-12-1421 minThe Effective Data ScientistHow to Write Impactful and Effective Emails While Avoiding Common Mistakes (Episode 20)
Do you have a lot of email ping-pong, where emails go back and forth many times – too many times?
Are you aware about the brand of you, that you communicate with your email style?
Is email your default communication tool?
Then this episode is for you. We have researched various articles on good email writing copies and distilled the best for you in this episode.
By listening to this episode, you will learn about:
When is email the best way to communicate?
Approaches to attachments.
How to take care of your style?
How to structure your emails?
About different email cu...2023-11-1734 minThe Effective Data ScientistTips and Tricks to Reduce Your Email Burden Including the Option of Last Resort (Episode 19)Discussion with Alexander Schacht and Benjamin Piske
By listening to this episode, you’ll learn about these topics:
What are helpful mindsets about emails
Five step approach to managing emails
Good habits to establish like
Reply in a timely manner
Send and respond less to receive less.
Tips on how to set up filters
Smartphone vs desktop email checking
When and when not to work on emails
And the option of last resort
2023-11-0230 minThe Effective Data ScientistData Visualization Part 2 (Episode 18)Discussion with Alexander Schacht and Paolo Eusebi
In this episode, we share out ideas and experiences, which mindset sets up statisticians for success. We cover topics around:2023-10-1923 minThe Effective Data ScientistData Visualization Part 1 (Episode 17)2023-10-0524 minThe Effective Data ScientistSuccess Starts in Your Head - Thoughts About the Mindset of Being Successful (Episode 16)Discussion with Alexander Schacht and Benjamin Piske
In this episode, we share our ideas and experiences, which mindset sets up for success. We cover topics around:
Leading people
Convincing business partners
Delivering value and selling it–and what does selling mean
Thinking outside the status quo to improve things in the long run
Always learning about the business and the people in the business
Learning about statistical innovation
Doing things more effectively
Becoming more impact-fully
Raising your business acumen–internally and exte...2023-09-2123 minThe Effective Data ScientistWhat Are the Questions to Ask If You Get a New Project? (Episode 15)2023-09-0621 minThe Effective Data ScientistA Picture Says More Than 1000 Tables (Episode 14)2023-07-1345 minThe Effective Data ScientistWriting Reproducible Reports using Quarto (Episode 13)Discussion with Paolo and Thomas
Communicating data is so important! Quarto is a fantastic tool for writing reproducible reports
using literate programming. Literate programming allows us to incorporate documentation and
code in the same program. The data science community has embraced this idea by adopting
Rmarkdown and Jupyter Notebooks. Using Quarto efficiently, you can create parametrized
reports, write scientific publications, and build data-driven slides.
Enjoy this super-interesting conversation with Thomas Neitmann, and be an effective data
scientist!2023-06-2916 minThe Effective Data ScientistSharing your Code with R Packages (Episode 12)In this episode, Paolo interviewed Thomas on why sharing your code with R packages for some data science projects is essential. When is it important? Where to start? What are the main steps and best practices? This skill could be a game-changer in your career as a data scientist, and nowadays, it’s much easier due to the introduction of new tools.2023-06-1522 minThe Effective Data ScientistHow to Effectively Structure Data Science Projects in R (Episode 11)
In this episode, Paolo and Thomas dive into the fundamental principles for a well-structured data science project. These include practical advice on:
• organizing files into folders,
• documenting and commenting code,
• using version control systems and much more.
Although the episode focuses on applying these fundamental principles in R projects, you want to apply the same principles to any Data Science project, regardless of the language used.
Further resources:
Advanced R 2nd Ed. (http://adv-r.hadley.nz)
R for Data Science 2nd Ed. (http://(r4ds.hadley...2023-06-0121 minThe Effective Data ScientistDichotomization and Proportional Odds Model (Episode 10)
In this episode, we move from the logistic regression model to proportional odds model, with emphasis on
interpretation and the checking of assumptions (visually and analytically). We also speak about the
opportunities and challenges of dealing with the dichotomization of ordinal or continuous variables.
Resources:
● McCullagh, Peter, and John A. Nelder. Generalized linear models. Routledge, 1983.
● Agresti, Alan. Categorical data analysis. John Wiley & Sons, 2003.
● Faraway, Julian J. Extending the linear model with R: generalized linear, mixed effects and
nonparametric regression models. Chapman and Hall/CRC, 2016. (http://https://julianfaraway.github.io/faraway/ELM/)2023-05-1815 minThe Effective Data ScientistLogistic regression (Episode 9)
Logistic regression is a beautiful tool for modeling a binary dependent variable, although many more
complex extensions exist. In the show, we will speak about the generalized linear model family, logit and
probit functions, interpretations, and practicalities.
Resources:
● McCullagh, Peter, and John A. Nelder. Generalized linear models. Routledge, 1983.
● Faraway, Julian J. Extending the linear model with R: generalized linear, mixed effects and
nonparametric regression models. Chapman and Hall/CRC, 2016. (http://https://julianfaraway.github.io/faraway/ELM/)2023-05-0816 minThe Effective Data Scientist3 steps to make your research more reproducible with Heidi Seibold (Episode 8)
Creating reproducible research is crucial for data scientists as it ensures transparency, understanding, and accuracy in the research process. Not only does it help others understand your work, but it also allows for the reproduction and verification of your results in the future.
Heidi Seibold, an expert in reproducible research, suggests three steps for achieving reproducibility:
Document everything
Develop reusable code, and
Share results with others.
By following these steps, you can ensure that your research is reproducible and accessible to anyone who needs it. Share this resource with your colleagues who want...2023-04-2133 minThe Effective Data ScientistThe art of communicating data with Hana Khan
Alexander interviewed Hana Khan about her path from being a data analyst to a data visualizer. Hana runs Hanalytx, her own company, which is specialized in helping others in presenting and visualizing data. Hana also runs the Art of Communicating Data podcast.
In this episode, Hana and Alexander discussed super interesting topics like sources of inspiration, optimal workflow, and appropriate tools for producing great data visualizations.2023-04-0530 minThe Effective Data ScientistBayesian inference and probabilistic programmingInterview with Alex Andorra
Interviewing Alex Andorra about bayesian inference, probabilistic programming, and more was a pleasure.Alex is a data scientist and modeler at the PyMC Labs consultancy. He's also an open-source enthusiast and core contributor to the python packages PyMC and ArviZ. Alex is also a contributor and instructor in the "Intuitive Bayes Introductory Course". This self-paced course is designed for data scientists and developers, where you'll learn Bayesian modeling with code, not math.Alex also runs the amazing "Learning Bayesian Statistics" podcast!If you love Python and Bayesian inference, catch this episode.2023-03-1049 minThe Effective Data ScientistEverything to know to write programs like a pro - Principles for good programming (Episode 5)Interview with Shafi Chowdhury
Click here to get the quick guide!
Shafi Chowdhury
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He has have over 20 years of experience as a statistical programmer in the Pharma industry. He worked for Pharma companies and CROs across Europe in many different therapeutic areas and in all phases of clinical trials before setting up his own consultancy firm. He believes knowledge should be shared and therefore he is a regular presenter at PhUSE conferences and regularly attend many other conferences including PSI conferences for Statisticians in...2023-02-0921 minThe Effective Data ScientistInterpretable ML with Serg Masis
Interpretable Machine Learning with Python - Second Ed
Interpretable Machine Learning with Python - Second Edition [link]
Explainable Boosting Machine [link]
How Interpretable and Trustworthy are GAMs? [link]SHAP (SHapley Additive exPlanations) [link]
2023-01-2647 minThe Effective Data ScientistBecome familiar with linear regression - Part 2 (Episode 3)In this episode, we continue to dive into the linear regression model. What are the real-world applications? When our model fit is enough? What are the pros and cons of increasing complexity in our model?
We discuss also the basic principles of covariates transformation (i.e. the logarithm) and how this has played a pivotal role in the modeling of the Covid-19 epidemics.
Furthermore, we discuss how to model and interpret interactions between covariates.
In this GitHub Repository, you will find R scripts helping to understand the basics of linear regression.2023-01-1230 minThe Effective Statistician - in association with PSIHow to analyse subgroups effectively using data visualisationInterview with Paolo Eusebi
In this episode, Paolo and I discuss the importance of visualisation in understanding subgroups. Specifically we speak about:
Why visualisation is importantHow to create effective visualisationGraphical display of subgroupsSubgroup explorerExploring robustness of subgroups between studies Three step approachMeta-analysis of interactionGraphic Display of Heterogeneity GOSH plotShiny App
Listen to this episode and share this with your friends and colleagues!
2022-03-1525 minThe Effective Data ScientistIntroduction to Linear Regression (Episode 2)2021-07-0725 minThe Effective Data ScientistWelcome to the effective data scientist podcast2021-07-0511 minThe Effective Statistician - in association with PSIHow to best visualize uncertaintyInterview with Paolo Eusebi
Interestingly, the visualization of uncertainty - one of the primary forms we use to communicate it - is a rather unknown field. In this episode, I'm very excited to speak with Paolo Eusebi, who has done research in this field to answer the following questions:
What can we learn from examples outside of medical research? How is it explained to the general public?What’s the current status in medical research?How can we become better in communication of uncertainty?What are further excellent resources regarding the display uncertainty?
Listen to this episode an...2021-01-1146 min