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Interpretable machine learning (IML) is rapidly gaining popularity in the data science community. It offers a new way to build and interpret models that are more transparent and understandable. In this episode, we have the privilege of interviewing Serg Masis. Serg authored the book “Interpretable Machine Learning with Python: Learn
When it comes to clinical trial design, there are many challenges to overcome, including recruitment, protocol design, and data analysis, among others. Fortunately, simulations can provide a solution to some of those challenges. Simulations allow us to test the influence of assumptions, optimize designs, and understand probabilities of success before
In today’s highly competitive work environment, developing leadership skills such as vulnerability and empathy will mean the difference between success and failure. In this podcast episode, Marius and I discuss Brené Brown’s “Dare to Lead”, a book that dives into the importance of vulnerability-based leadership. This episode will explore some of the
The field of statistics is rapidly growing, and statisticians play an important role in providing a competitive advantage to companies. However, finding the right job or candidate for a position can be challenging. That’s where Clivoffective comes in – a collaboration between Clivolution and The Effective Statistician focused on connecting
In the field of statistics, we need specific skills necessary for being successfull. Debarshi Dey, currently the head of the Statistics and Programming and Data Management department at Morphosys, has spent the past 13 years in the pharmaceutical industry. With a PhD in statistics from UC Riverside, Debarshi believes that
We statisticians have always been important for brining new therapies to patients. We design experiments, analyze and interpret data to provide valuable insights that can help make informed decisions. However, the value of our work increases if we’re able to lead others. But becoming an inspirational statistician requires more than
Are you a statistician or data scientist looking to excel in your career and make an impact in the healthcare industry? Today’s episode is inspired by a German podcast that delved into five key reasons for career failure and I fine-tuned this to fit statisticians. As professionals working with complex projects and
If you’re a statistician, data scientist, or programmer looking for quality training opportunities that will help you advance your career, you might want to look into The Effective Statistician Academy. This exclusive academy offers a range of courses that cover essential topics in the field of statistics. From leadership to
What strategies do you use in your work as a statistician to ensure successful outcomes? How do you set expectations with stakeholders when tackling a project?Are there any common mistakes statisticians make when setting expectations in their job that you have learned to avoid?How setting realistic expectations can positively impact
What knowledge gaps exist regarding the implementation of these new analytical techniques, and how can statisticians and data scientists bridge them to maximize effectiveness of clinical research? Despite the promises of Bayesian approaches, the lack of expert training, software tools, and computational resources has made their adoption slow. Statisticians and
As statisticians, we rely on good quality from programmers and data management. And if you talk to your colleagues, everybody has a story about a poor experience. But the questions are: How do we collaborate with other departments to create a quality deliverables?How to strike the right balance between working
For years, creating data visualizations has frustrated statisticians, data analysts and data scientists. Software – especially SAS – hasn’t been great and organisation have tried to take the pain out of the process by creating standard figures. But these standard graphics fail to communicate the message to the intended audience
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