Beyond the Basics: Key Statistical Methods and Career Strategies for Data Analysts | Mavens of Data

If you were only going to learn a few statistical techniques as an analyst, where should you focus?

Josh Starmer, Founder of StatQuest, shares how learning these skills can boost your career. We dive into why linear regression is the bedrock for advanced statistical tests like the t-test, and why understanding Principal Component Analysis (PCA) can give you an edge in working with complex datasets.

But it’s not just about the math—we also explore how expanding your skill set beyond the numbers can make you a stronger candidate for promotions and new roles.

From building a diverse portfolio of skills to positioning yourself effectively in quarterly reviews, we discuss strategies to ensure you stand out in your organization and the broader job market.

Whether you’re early in your data career or looking to sharpen your expertise, this episode gives you actionable insights to grow both technically and professionally.

What You'll Learn:
1) Core statistical methods every analyst should know, including why linear regression is the foundation for advanced analytics
2)How learning tangential skills like Principal Component Analysis (PCA) can set you apart in the field
3) Positioning yourself for success in quarterly reviews and career conversations

Be sure to check out Josh’s Illustrated Guide to Machine Learning and his YouTube channel ‪@statquest‬!
📚: https://a.co/d/goj9V4U

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