The Effective Statistician - in association with PSI
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The podcast from statisticians for statisticians to have a bigger impact at work. This podcast is set up in association with PSI - Promoting Statistical Insight. This podcast helps you to grow your leadership skills, learn about ongoing discussions in the scientific community, build you knowledge about the health sector and be more efficient at work. This podcast helps statisticians at all levels with and without management experience. It is targeted towards the health, but lots of topics will be important for the wider data scientists community.
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pisode Summary In this episode of The Effective Statistician, Alun Bedding speaks with Emma May about the skills that truly differentiate effective statisticians from great leaders. While technical expertise remains essential, success in today’s environment increasingly depends on the ability to build trust, communicate effectively, and lead with emotional intelligence. Drawing from their joint leadership workshops, Alun and Emma explore how statisticians can develop these capabilities and apply them in real-world settings. They discuss practical approaches to creating psychological safety, shifting from a “telling” to a coaching mindset, and fostering a growth mindset within teams. The conversation highlights why leadership is not about having all the answers—but about enabling others to contribute, grow, and succeed.
Generative AI is moving fast—and in pharma, it’s no longer just a buzzword. In this episode of The Effective Statistician Podcast, I speak with Manuel Cossio about how Generative AI is already being applied in real-world pharma settings, where it’s delivering value today, and what still needs careful consideration in regulated environments. Manuel brings a unique hybrid background, combining molecular biology, genetics, pharma experience, and deep AI engineering expertise. He works at the cutting edge of AI in clinical development, including agentic systems, human-in-the-loop approaches, and large-scale document automation. This conversation goes well beyond theory. We focus on practical use cases, real limitations, and how statisticians, programmers, and data scientists can responsibly use GenAI to become more effective.
As we start 2026, I want to take a moment to express my sincere gratitude to everyone who has been part of The Effective Statistician podcast. This episode features my co-host, Alun Bedding, reflecting on the past year and sharing thanks on behalf of both of us. From our listeners who tune in, share episodes, and engage with the content, to our guests who generously share their expertise and real-world experiences — your participation makes this podcast both insightful and practical for statisticians worldwide. I also want to recognize Reine and her production team. So much of the work that brings each episode to life happens behind the scenes, and we are deeply grateful for their professionalism and dedication. We’re excited about what 2026 has in store. I look forward to continuing this journey with all of you and bringing even more valuable conversations to our community.
In this episode, I talk with my long-time friend and frequent guest, Kaspar Rufibach, about a skill that quietly determines how much impact we really have: presenting and communicating our work. We walk through how Kaspar prepares his talks (including why he starts months in advance), how he structures messages so stakeholders actually remember and act on them, and why overcrowded slides are often just a sign that we haven’t done the hard thinking yet. We also get honest about something many statisticians feel but rarely discuss: the fear of public speaking, the frustration of bad meetings, and the “personal brand” you build every time you present—whether you intend to or not. If you’ve ever walked out of a meeting thinking “I don’t think they really understood what I meant,” this episode is for you.
In this episode, I’m joined by Deepa Jahagirdar, Associate Research Principal at Cytel, to explore what it really takes to build a good external control arm (ECA). Deepa brings a fascinating background from social epidemiology, where causal questions often need to be answered without running randomized trials. That experience translates directly into today’s growing need for ECAs, especially when we rely on real-world data to support single-arm trials, extension phases, or situations where randomization simply isn’t possible. Together, we discuss how to choose the right data source, how target trial emulation works in practice, what to do about confounding, and how to judge whether an ECA is truly robust. If you’re working with real-world evidence, complex study designs, or causal inference, this episode will give you clarity and confidence in approaching ECAs the right way.
Why this episode made our all-time Top 9: If you’ve ever thought “non-parametric = Wilcoxon/Mann-Whitney and that’s it,” this conversation will happily destroy that myth. Frank shows how rank-based methods unlock rigorous analyses for skewed data, outliers, ordinal endpoints, small samples, composites/estimands—and how to communicate effects without relying on means.
Adaptive designs let us learn earlier, stop smarter, and protect patients—but they also make communication tricky. In this episode, Kaspar Rufibach and I dig into what “still correct” looks like when you try to explain results from group-sequential and other adaptive trials to regulators, clinicians, and scientific audiences. We unpack conditional vs. unconditional bias, median-unbiased estimation, stage-wise ordering for p-values, confidence intervals in multi-stage settings, and what to do with secondary endpoints and multiplicity. We also touch on ICHE20 (Adaptive Clinical Trials) and why pre-specification isn’t just a box-tick—it’s what builds trust.
In this episode, I’m joined once again by my friend and frequent guest, Kaspar Rufibach, to talk about a topic that’s been around for decades but is gaining fresh attention thanks to the new ICH E20 draft guideline—adaptive designs in confirmatory clinical trials. Kaspar and I discuss why and when we should consider adapting a clinical trial, what kinds of adaptations are statistically valid and meaningful in a regulatory context, and why these designs—despite their efficiency—are still not used as often as they could be. We also dive into the statistical foundations behind adaptive designs, such as p-value combination methods and meta-analytic thinking, and explore how adaptive approaches can help us make faster and smarter decisions in drug development.
This episode is a little different because Alun turns the microphone toward me. After 456 episodes, it feels both strange and exciting to be the “guest” on my own show. Together, we reflect on the journey so far and then dive into a topic close to both our hearts: the human skills that make statisticians and quantitative scientists truly effective. We talk about leadership as helping others accomplish something, how to influence people across functions (not just departments), why being known inside your organization matters, and how presentation skills can make or break your impact. We wrap up with three actions you can start applying right away.
I’m excited to reshare one of our most-played conversations—the one where Norwegian regulator/HTA leader Anja Schiel and I get very practical about when single-arm trials fail decision-makers and what comparative, smarter alternatives look like for regulators, HTA bodies, payers, clinicians, and—most importantly—patients.
As statisticians in pharma, one of the most important professional relationships we can build is with our physician colleagues. When this partnership works well, studies run smoother, decisions are better, and our impact for patients grows. In this all-time Top 7 replay, Benjamin Piske and I talk about what makes this collaboration effective, the challenges you may face, and how to establish yourself as a true partner rather than “just the statistician.”
This is one of our most downloaded episodes ever, and I’m excited to bring it back in this replay. In this conversation, I spoke with Lara Wolfson (MSD) and Anders Gorst-Rasmussen (Novo Nordisk) about EU HTA (European Union Health Technology Assessment): what it is, why it’s coming, and why statisticians like us must pay attention. If you’ve ever wondered whether your approach to safety analysis is leading to misleading conclusions, this episode is a must-listen.
We’re bringing back one of our most downloaded episodes ever – a deep dive into how adverse events should be analyzed properly. This conversation with Jan Beyersmann and Kaspar Rufibach is packed with methodological insights and practical implications for statisticians working in clinical trials. Adverse event (AE) analysis has long been approached differently from efficacy analysis, often using overly simplistic methods that can bias results. In this episode, we discuss why that’s a problem – and how the SAVVY collaboration (Survival analysis for AdVerse events with Varying follow-up times) is pushing the field forward. Together with academia and multiple pharma companies, this collaboration tackled the issue of AE analysis using real randomized trial data, not just simulations. The findings show how common methods can underestimate or overestimate event probabilities and how established statistical methods can be applied more consistently to ensure fair benefit–risk assessments. If you’ve ever wondered whether your approach to safety analysis is leading to misleading conclusions, this episode is a must-listen.
In this special replay of one of our all-time most popular episodes, we dive deep into one of the most debated topics in the pharmaceutical industry: R vs SAS. Together with Thomas Neitmann and my co-host Sam Gardner, we compare these two powerful statistical programming tools from multiple angles — ease of learning, day-to-day usability, community support, visualization capabilities, regulatory acceptance, and more. Whether you are a seasoned SAS programmer, an R enthusiast, or someone deciding which tool to focus on, this conversation will give you valuable insights into where each shines, where they struggle, and how the industry is evolving.
In this special replay episode — the top 3 most downloaded of all time — I’m again joined by Stuart McGuire as we explore The Chimp Paradox by Professor Steve Peters. This book provides a simple yet powerful model for understanding how our brain works — and how it often works against us if we’re not aware of it. Whether in meetings, under pressure, or dealing with self-doubt, understanding your inner “chimp” can help you manage emotions, lead with clarity, and avoid the traps that keep so many statisticians and scientists stuck. This episode remains a favorite because it strikes at the core of how we think, react, and lead — especially in high-stakes scientific and business environments.
This episode ranks as the #2 most downloaded of all time—and for good reason. As data science continues to disrupt and redefine the healthcare and pharmaceutical industries, statisticians everywhere are asking: Where do I fit in? In this insightful conversation, two leaders from Cytel—Yannis Jemiai, Head of Consulting and Software, and Rajat Mukherjee, Head of Data Science—share their personal journeys from traditional statistics into data science, how the field is evolving, and why statisticians are uniquely positioned to lead the future of analytics in life sciences. Whether you're curious, skeptical, or already exploring data science, this episode will inspire and equip you with practical insights.
This episode originally struck a chord with statisticians around the world—and for good reason. Whether you’re just starting with real-world evidence (RWE) or mentoring someone who is, this conversation is packed with practical lessons that will help you navigate the complexities of observational data with more confidence. In this special replay, guest Rachel Tham and I reflect on the real-world analysis mistakes, misconceptions, and growing pains they wish someone had warned them about earlier in their careers. From ambiguous index dates to messy exposure definitions and unexpected data quirks—this episode will save you hours of rework and help you better manage timelines and expectations.
In this thought-provoking keynote recording, Manjari Narayan takes us on a journey through one of the most pressing and promising intersections in modern science: the convergence of artificial intelligence, statistics, and biotechnology. Drawing on her extensive experience in both academia and biotech startups, Manjari explores the critical role statisticians can play in AI-driven drug discovery, biomarker validation, and experimental design. We are living in a "Cambrian explosion" of biotechnology, where high-throughput experiments, protein engineering, humanized models, and AI-powered screening open massive opportunities—but also introduce challenges in scientific validity, reproducibility, and decision-making. Through personal vignettes and cutting-edge examples, Manjari lays out how statistical thinking can (and should) drive better outcomes in early-stage drug development, biomarker discovery, and translational model evaluation. This episode is a must-listen for statisticians, data scientists, and healthcare innovators navigating the rapidly evolving biotech and AI startup landscape.
In this special keynote episode, I’m excited to share the recording of Professor Tim Friede’s thought-provoking presentation from The Effective Statistician Conference 2024. Tim, a leading expert in biostatistics and clinical trial design, dives deep into the combination of randomized controlled trials (RCTs) and real-world data (RWD)—especially in the context of rare diseases. Drawing from his work at the University Medical Center Göttingen and numerous European research initiatives, Tim presents a compelling case for integrating RWD to support small or underpowered RCTs using advanced statistical models. He shares real-world examples (including CJD and Alport syndrome), simulation insights, and practical recommendations that can change how we approach evidence generation in low-prevalence populations. What You’ll Learn:
In this keynote episode, Professor Sebastian Schneeweiss from Harvard Medical School shares groundbreaking insights from his extensive research into emulating randomized controlled trials (RCTs) using real-world data (RWD). Recorded live at The Effective Statistician Conference 2024, this talk explores whether non-randomized studies based on electronic health records and claims data can reach conclusions as reliable as those from traditional RCTs. Prof. Schneeweiss, also Chief of the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women’s Hospital, walks us through the RCT DUPLICATE project, a major FDA-funded initiative that evaluated whether regulatory decisions could be replicated through high-quality real-world evidence (RWE). From the successes to the limitations—and everything in between—this episode is packed with lessons for statisticians, regulators, and pharmaceutical leaders interested in the future of data-driven healthcare decisions.
In this episode of The Effective Statistician, Alun Bedding takes the mic to explore one of the most underrated yet transformative tools in any professional's career—networking. With the PSI Conference happening, this episode offers timely insights into how statisticians—introverts and extroverts alike—can use networking to build meaningful professional relationships, accelerate their careers, and find support within the broader community. Alun shares personal anecdotes, including how a casual conversation with Alexander at a past PSI event led to his current guest host role, and outlines a step-by-step mindset and strategy for networking with authenticity and purpose.
In this episode, Alun Bedding welcomes Emma Crawford for a powerful and personal conversation about building inclusive workplace cultures—ones where every individual can thrive. Emma shares her late diagnosis of autism and how it reshaped her experience and expectations of the workplace. Together, they explore the limitations of the traditional “reasonable adjustments” framework and introduce the concept of success enablers—workplace strategies and tools that benefit not just neurodivergent individuals but everyone on the team. The conversation dives deep into the role of leadership, AI tools, flexible work arrangements, and cultural shifts that prioritize accessibility and well-being for all employees. Emma also previews her interactive workshop at the upcoming PSI conference and gives insight into how the session will encourage open discussion, hands-on activities, and actionable takeaways to help leaders and teams foster a more inclusive environment. Whether you’re a people leader, statistician, or advocate for change—this episode will challenge your assumptions and inspire more inclusive practices.
How can oncologists and healthcare professionals keep up with the ever-growing body of research to make the best decisions for patients? In this episode, I speak with Anna Forsythe, a pharmacologist, health economist, and founder of OncoScope, a groundbreaking platform delivering daily updated systematic literature reviews (SLRs) in oncology. Drawing on decades of experience in pharma and health economics, Anna shares how automation and AI are transforming the traditionally tedious SLR process—making up-to-date evidence accessible to clinicians in just a few clicks. Anna’s vision is clear: democratize access to high-quality, current evidence for clinicians—and ultimately improve patient care.
In this episode, I’m joined by Julia Geronimi from Servier and Dr. Pavel Mozgunov from the University of Cambridge to explore a topic that’s absolutely central to advancing precision medicine—predictive biomarkers. We dive into the challenges of identifying predictive vs. prognostic biomarkers, especially in early-phase clinical trials with limited sample sizes. What makes their approach so exciting is that it offers a model-flexible, visually intuitive way to detect predictiveness—even before we talk about dichotomizing biomarkers or setting cutoffs. If you work on clinical trial design, translational science, or biomarker development, this conversation will give you fresh tools—and a lot to think about.
In this special episode, I’m sharing the recording of a webinar I co-hosted with Cytel on March 20, 2025. I was joined by an expert panel of leaders in statistics and clinical development: Yannis Jemiai, Flaminia Chiesa, and Benjamin Piske. Together, we explored how the role of statisticians is rapidly evolving in response to industry changes, data innovations, and AI-driven transformation. This rich discussion dives into what it means to lead as a Clinical Data Scientist today—and why statisticians are uniquely positioned to influence strategy, innovation, and decision-making across the healthcare and pharmaceutical sectors.
In this episode, I’m excited to welcome back Katrin Kupas, a statistician with deep expertise in Health Technology Assessment (HTA) and real world evidence (RWE). We dive into how RWE and the new Joint Clinical Assessment (JCA) process in Europe can work together—and where the challenges lie. As the JCA becomes more central in EU regulatory and reimbursement discussions, knowing how and when to use real world data is critical. Katrin shares practical use cases, methodological guidance, and strategic insights for integrating RWE into early planning.
As someone who found my way into statistics late—only halfway through university—I often wonder: what if more young people knew about this path earlier? In this episode, I sit down with two wonderful guests and PSI volunteers, Emma Crawford and Alex Spiers, to explore exactly that: how we, as statisticians and scientists, can inspire the next generation. We talk about the why behind investing in STEM outreach, share personal stories, and get into the practical steps you can take—whether you want to volunteer at a school, present virtually, or simply start a conversation with a student.
Group sequential trials, interim analyses, final analyses, updated analyses… what do these terms actually mean, and why is there so much confusion? In this technical yet highly practical episode, I speak with Kaspar Rufibach, Principal Biostatistician at Roche, to unpack some of the most commonly misunderstood terminology and concepts in clinical trial design and analysis. If you've ever questioned what really qualifies as an "interim analysis" or struggled to explain why a “final analysis” isn’t always the last word, this conversation is for you.
In this episode, I had the pleasure of speaking with Prof. Holger Fröhlich, who leads the AI and Data Science Group at the Fraunhofer Institute and is an honorary professor at the University of Bonn. We explored one of the hottest topics in healthcare data science right now: synthetic data. Holger and I discussed how synthetic data is generated using AI, what role digital twins could play in the future of clinical trials, and how these innovations could fundamentally reshape how we design and conduct research. We dove into the Cynthia Project, which is part of the Innovative Health Initiative (IHI) – the largest public-private partnership for health research in Europe.
In this episode, I’m diving into a topic that’s very personal to me—working in an English-speaking environment as a non-native speaker. If you’ve ever felt unsure about your English skills in meetings, emails, or presentations, you’re not alone. I’ve been there myself, and I want to share what’s helped me grow more confident and effective over the years. I’ll walk you through practical strategies that go beyond grammar—things that have really made a difference for me in both speaking and writing, and most importantly, in getting my message across clearly.
In this episode, I’m once again joined by Daniel Sabanés Bové for a deep dive into one of the most impactful tools for statisticians working with data visualization—R-Shiny. We explore how interactive data visualizations can help you iterate faster, collaborate better across functions, and focus more on the actual scientific questions rather than just coding. Daniel shares some excellent examples from clinical trials and gives practical tips on how to avoid common pitfalls when building Shiny apps. Whether you're designing your first app or maintaining a more complex one, you'll find plenty of value in this conversation—from best practices around UI/UX design to strategies for modular development and testing.
In this episode, I’m sharing three personal stories where soft skills—or better yet, human skills—made a huge difference in my work as a statistician. Whether it was building trust to access critical data, presenting results in a way that truly resonated, or negotiating a fair contract, these experiences reminded me how essential these skills are alongside our technical expertise.
In this episode, I’m joined once again by Daniel Sabanés Bové to talk all about R packages—why they’re so useful, when to create one, and how to do it effectively. Whether you’re just starting out with writing reusable functions or thinking about building a more robust and reusable R package, you’ll find plenty of hands-on advice in our discussion. Daniel shares his experiences from working at Roche, Google, and now through his consultancy, Arconis. We dive into everything from writing clean and consistent code, to testing, documenting, and even promoting your package in the open-source world. What You’ll Learn in This Episode:
In this episode, I welcome back Necdet Gunsoy, who’s now in a new role as the founder of EviMed, a boutique consultancy specializing in health economics, outcomes research, real-world evidence, and market access. We dive into the often tense relationship between statisticians and market access professionals, exploring why these functions struggle to collaborate and, more importantly, how we can work together more effectively.
In this episode of The Effective Statistician podcast, I dive into the art of persuasion. As statisticians and data scientists, we often rely on logic and data, but true influence requires more than just being right. Drawing from ancient Greek philosophy, I explore the three pillars of persuasion—ethos (credibility), logos (logic), and pathos (emotion)—and share practical strategies to help you effectively convince others. Whether you are presenting new methodologies, influencing key stakeholders, or advocating for change, this episode will equip you with essential communication skills to make a lasting impact.
In this episode of The Effective Statistician, I sit down with Kaspar Rufibach to tackle a topic that affects statisticians every day—how to interpret p-values, confidence intervals, and statistical hypotheses. We explore the differences between Fisher’s and Neyman-Pearson’s approaches, clear up common misconceptions, and discuss how misinterpreting statistical significance can lead to flawed conclusions. Using real-world examples from clinical trials and drug development, we highlight best practices for communicating statistical results effectively. Whether you're working with clinicians or business stakeholders, this episode will help you gain clarity on these fundamental statistical concepts and use them correctly in your daily work.
In this episode of The Effective Statistician, I dive into a crucial skill—building influence within a clinical trial team. As statisticians, we often need to negotiate timelines, advocate for better analysis methods, and ensure clear communication across teams. The stronger our influence, the more impact we can have on study outcomes and, ultimately, patients. I break down the key pillars of trust—care, character, and competence—and share practical strategies to help you collaborate effectively, align team priorities, and proactively tackle challenges. Tune in and start building your influence today!
I know firsthand how challenging it can be to manage a heavy workload while maintaining mental well-being. In this episode of The Effective Statistician, I talk with Peter Wehmeier about the five key dimensions of self-management—building strong relationships, setting priorities, making decisions, and taking action. We share practical strategies to reduce stress, strengthen resilience, and take control of both work and life. With insights from Peter’s upcoming workshops, this conversation offers valuable tools to help you stay balanced and productive. Tune in to learn how to take charge of your future!
Welcome to another episode of The Effective Statistician! Today, I sit down with Darko Medin to explore how artificial intelligence is transforming biostatistics. Darko works as a biostatistician for companies worldwide and builds digital solutions that push AI’s boundaries. We dive into Bio AI Works, the platform he’s developing to improve AI reliability and eliminate issues like hallucinations in large language models. Darko explains how AI can enhance statistical accuracy, uncover hidden data patterns, and accelerate breakthroughs in oncology and precision medicine. If you want to understand how AI can revolutionize biostatistics while maintaining scientific rigor, this episode is for you. Let’s get started!
In this episode of The Effective Statistician, I explore Slow Productivity by Cal Newport—a book that challenges how we think about work and efficiency. I welcome Alun Bedding and Steve Mallett to discuss how statisticians can apply Newport’s principles: doing fewer things, working at a natural pace, and obsessing over quality. We share our experiences with managing workloads, cutting unnecessary meetings, and focusing on meaningful work. If you want to break free from the busyness trap and boost your impact, this episode is for you.
In this episode of The Effective Statistician, I talk with Justin Belair about the process of writing a book on causal inference, one of the hottest topics in statistics. Justin explains how he discovered causal inference, what motivated him to write a hands-on technical book, and how he balances theory, real-world applications, and coding exercises. Having written a book myself, I know the challenges firsthand, so we dive into the strategies that make writing more effective. If you want to learn more about causal inference, apply practical tools in your work, or even write a book yourself, this episode has plenty of insights and inspiration. Tune in and join the conversation!
In this episode of The Effective Statistician, I introduce the Medical Data Leaders Community (MDLC)—a powerful new resource for statisticians, data scientists, programmers, and other quantitative professionals in healthcare research. I created this community to help you build and refine your leadership skills, so you can increase your influence and drive better decision-making in your organization. Leadership growth requires continuous learning, practice, and reflection, and MDLC provides the tools to support you every step of the way. Through workshops, peer mentoring, and real-world applications, you’ll develop strategic thinking, negotiation skills, and a stronger leadership presence. If you want to take your career to the next level, this episode will show you how MDLC can help.
Do you ever feel like your to-do list keeps growing no matter how much you check off? I’ve been there—busy all day but still feeling unproductive and overwhelmed. In this episode of The Effective Statistician, I share practical strategies to help you take back control. You'll learn why to-do lists spiral out of control, how to use the “single bridge system” to manage tasks efficiently, and how prioritization, delegation, and leadership skills can transform the way you work. If you’re ready to break free from endless tasks and start making real progress, this episode is for you!
In this episode of The Effective Statistician, I tackle the challenge of a packed calendar head-on. If back-to-back meetings, endless calls, and constant interruptions leave you with no time for deep, meaningful work, you’re not alone. I once averaged 37 meetings per week, so I know exactly how overwhelming it feels. I break down why our calendars spiral out of control, the real cost of this nonstop busyness, and, most importantly, three actionable strategies to reclaim your time. If you’re ready to take charge of your schedule and work smarter—not just harder—this episode is for you!
In this episode of The Effective Statistician, I tackle a challenge that many of us face—working long hours and feeling stuck in an endless cycle of pressure and expectations. I’ve spoken to countless professionals who struggle with ever-growing workloads, limited resources, and rigid workplace structures that make it difficult to work more efficiently. But the real issue isn’t just about managing tasks better—it’s about shifting the way we think about work. Here, I break down the limiting beliefs that keep us trapped, like equating our value with how hard we work, mistaking busyness for productivity, and chasing perfection at the expense of progress. Join me as I share strategies to work smarter, achieve more, and create a healthier work-life balance. Plus, I’ll tell you about an upcoming free webinar where I’ll dive even deeper into how you can become a more effective statistician while still enjoying life outside of work.
In this episode of The Effective Statistician, I explore how GAMS—the General Algebraic Modeling System—can solve complex optimization problems and transform how you approach modeling. I talk with Steve Dirkse, an expert who explains how GAMS simplifies challenges in logistics, healthcare, and beyond. Unlike generalized additive models, GAMS uses an algebraic modeling language to handle intricate systems with ease. Together, we uncover how you can start using this powerful tool, access its resources, and apply it to real-world scenarios. Join me as we dive into this fascinating topic and uncover how GAMS can make a difference in your work!
Are you tired of rushing through endless meetings, juggling countless tasks, and feeling like the grind never stops? Do you wonder if all this hustle is worth the toll it’s taking on your health, relationships, and happiness? In this episode of The Effective Statistician, I challenge the unsustainable culture of constant hustle and offer a better path: long-haul leadership. I’ll show you how focusing on personal growth, prioritizing your well-being, and building meaningful connections can help you break free from the burnout cycle. Let’s explore how to create a career that’s not only impactful but also sustainable for the long run.
Welcome to another episode of The Effective Statistician podcast! Today, I tackle the essential skill of negotiation—a tool we statisticians use every day, often without realizing it. We negotiate when we push for better study designs, adjust project timelines, or secure resources like training and conference budgets. Beyond work, we negotiate in our personal lives with family, friends, or vendors. In this episode, I share proven strategies to prepare for negotiations, uncover interests behind positions, and confidently advocate for yourself and your work. Mastering these skills empowers you to drive success and create a bigger impact as a statistician. Let’s jump in!
In this Friday edition of The Effective Statistician, Alun Bedding takes center stage to discuss a topic central to leadership and personal influence: Trust. With his characteristic insight and practical approach, Alun explores how trust forms the foundation of effective leadership, regardless of one’s title or position. Drawing on real-world examples and actionable strategies, he highlights the habits and choices that help build trust, foster authenticity, and inspire those around us. Whether you consider yourself a leader or not, this episode will challenge you to think differently about your role and influence. Tune in and discover how trust can transform your personal and professional life.