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.…

Interview with Shafi ChowdhuryIn 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 a…

Discussion with Alexander Schacht and Paolo Eusebi 000000E2 000000E0 00002DDD 00002879 000099FA 0000A568 00007FBA 00006CBA 00004C39 0000A224By Alexander Schacht and Paolo Eusebi

Discussion with Alexander Schacht and Paolo Eusebi 0000016B 0000015F 000045CA 00003CF4 0013891F 000E045E 00007FBA 00006E82 00004C39 001366D6By Alexander Schacht and Paolo Eusebi

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 th…

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 check…

Discussion with Alexander Schacht and Paolo EusebiIn this episode, we share out ideas and experiences, which mindset sets up statisticians for success. We cover topics around:By Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry

By Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry

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 …

By Alexander Schacht and Paolo Eusebi

By Gyom

Discussion with Paolo and ThomasCommunicating data is so important! Quarto is a fantastic tool for writing reproducible reportsusing literate programming. Literate programming allows us to incorporate documentation andcode in the same program. The data science community has embraced this idea by adoptingRmarkdown and Jupyter Notebooks. Using Quarto…

Resources: R Packages (2e)By Alexander Schacht and Paolo Eusebi

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, …

In this episode, we move from the logistic regression model to proportional odds model, with emphasis oninterpretation and the checking of assumptions (visually and analytically). We also speak about theopportunities and challenges of dealing with the dichotomization of ordinal or continuous variables. Resources: ● McCullagh, Peter, and John A. Nel…

Logistic regression is a beautiful tool for modeling a binary dependent variable, although many morecomplex extensions exist. In the show, we will speak about the generalized linear model family, logit andprobit functions, interpretations, and practicalities. Resources: ● McCullagh, Peter, and John A. Nelder. Generalized linear models. Routledge, 1…

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 st…

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 in…

Interview 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 "Intui…

Interview with Shafi Chowdhury Click here to get the quick guide! Shafi ChowdhuryThis image has an empty alt attribute; its file name is shaffi.webpHe 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…

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]By Gyom

Other resources: Linear Models with R by Julian J. Faraway, 2nd EditionRegression Modeling Strategies by Frank E. HarrellBy Gyom

By Introduction to Linear Regression - Part 1

By Gyom