Beyond the Codes with Lennon

  The Art of Asking the Right Data Question You've collected terabytes of data, mastered multiple programming languages, and can build complex models in your sleep. But here's the uncomfortable truth: none of that matters if you're asking the wrong question. The most sophisticated analysis answering the wrong question is just expensive noise. Let's master the most underrated skill in data science—asking the right question from the start. The Foundation: Why Your Question Matters More Than Your Data The Cost of Wrong Questions Starting with a poorly defined research question leads to: Wasted resources – Months of work analyzing irrelevant data Misleading conclusions – Answers that don't address the real problem Stakeholder frustration – Deliverables that miss the mark ⚠️ Warning: A brilliant analysis of the wrong question is worse than no analysis at all—it creates false confidence in bad decisions. Pro tip: Spend 20% of your project time crafting t...

  Why Statistics Still Matter in the Age of AI In an era where AI models can generate art, write code, and predict outcomes with stunning accuracy, you might wonder: do we still need statistics? The answer is a resounding yes! While AI and machine learning dominate headlines, statistical thinking remains the bedrock of reliable data science, reproducible research, and trustworthy insights. Let's explore why statistics isn't just relevant—it's essential—even as AI continues to evolve. The Foundation: Statistics Powers Everything in Data Science Why Statistical Thinking Is More Important Than Ever Despite the rise of complex AI models, statistics remains crucial because: Understanding beats black boxes – Statistical knowledge helps you interpret what models are actually doing Validation requires rigor – You can't trust model results without statistical testing and validation Reproducibility demands precision – Statistical methods ensure your findings can be r...

  Choosing the Right Statistical Test is Easy If You Know What to Check First You're in the data analysis section of your research and you get stuck choosing between a ton of statistical tests . Worry not! This guide shows the simple steps you need to determine which test is right for your analysis. Got questions? Feel free to reach out in the comments below! The Art of Choosing the Right Statistical Test Why Is Choosing the Right Test Important? Selecting the appropriate statistical test is crucial for your research integrity. The right test ensures: Accurate results that reflect your data truthfully Valid conclusions that stand up to scrutiny Reliable decision-making based on sound evidence ⚠️ Warning: Misusing a test can lead to incorrect interpretations and flawed outcomes that could invalidate your entire study. Pro tip: Always start with your research question and data type—these are your guiding stars! Ask Yourself These Questions Before Choosing a Test ...