🧪 DTSP Data Analyst S53: The Scientific Method for Data Analysis (EDA vs CDA) скачать в хорошем качестве

🧪 DTSP Data Analyst S53: The Scientific Method for Data Analysis (EDA vs CDA)

How do you turn a hunch into a fact? By following a structured, scientific process. This is your definitive guide to Skill S53 for the Digital & Technology Solutions Professional (DTSP) apprenticeship, focused on the core mindsets of a professional data analyst. Join expert tutor Sam as he demystifies the two crucial approaches to analysis: Exploratory (the detective work) and Confirmatory (the scientific test). This session is tailored for Data Analyst apprentices who need a clear, logical, and repeatable framework to produce trustworthy and validated insights with confidence. IN THIS VIDEO: ✅ A clear breakdown of Exploratory Data Analysis (EDA) - the art of finding patterns and generating hypotheses. ✅ A practical guide to Confirmatory Data Analysis (CDA) - the science of rigorously testing your hypotheses. ✅ Why "Validate and test stability" is the most crucial step for building trust and credibility in your work. ✅ The gold-standard technique for validation: the Train/Test Split, explained in simple terms. ✅ A real-world case study showing the end-to-end process of analyzing an A/B test. ✅ A powerful portfolio task to help you apply this professional, rigorous mindset to your own work. This presentation aligns perfectly with the ST0119 v1.2 standard. Stop just finding patterns and start proving them with a process you can trust. ADDITIONAL DETAILS: Your problem, solved! Find the exact answers you need below: Slide 2: What is the difference between Exploratory and Confirmatory analysis? Slide 4: How do I generate a hypothesis? Slide 5: How do I test a hypothesis? Slide 6: What is data validation and why do I need it? Slide 9: How do I evidence S53 in my portfolio? ➡️ Download the full presentation slides and transcript from our EPA Hub: www.mentorinai.com/epahub/ Timestamps: 00:00 Introduction - The Scientific Method for Data 01:30 Deconstructing the Skill - A Path to a Reliable Answer 02:45 The 'Why' - The Foundation of Your Credibility 04:00 The Exploratory Approach: The Detective 05:15 The Confirmatory Approach: The Scientist 06:30 The Final Step: Validation (Train/Test Split) 07:45 S53 in Action: A/B Test Analysis 09:00 Documenting Your Process: The Analysis Log 10:15 Your Turn - The Two-Mindsets Plan (STARR) 11:30 Implementing S53 in Your Major Project 12:45 Conclusion - The Rigorous Analyst EPA Checklist: The S53 "What, How, Why" What: Did I clearly distinguish between my initial exploration and my formal testing? How: Did I use a statistical test or a validation method (like splitting data) to confirm results? Why: Did I explain that this rigour ensures the stability and trustworthiness of the business insight? Affiliate Links: Enhance your Data Analysis skills with these recommended courses: Coursera: Google Data Analytics Professional Certificate Pluralsight: Data Science with Python (We may earn a commission if you sign up through these links). Join our newsletter for weekly tips: www.mentorinai.com Need help? Book a Mock Interview or Portfolio Review today!