Top 5 Statistics Concepts in Data Science Interviews: P-value, Confidence Interval, Power, Errors

Top 5 Statistics Concepts in Data Science Interviews In this video, we will talk about the top 5 statistics concepts in Data Science interviews. I will show you how to explain those concept to both technical and non-technical audiences. Typos 10:09 "hull" hypothesis should be "null" hypothesis ?Get all my free data science interview resources https://www.emmading.com/resources ? Product Case Interview Cheatsheet https://www.emmading.com/product-case-cheat-sheet ? Statistics Interview Cheatsheet https://www.emmading.com/statistics-interview-cheat-sheet ? Behavioral Interview Cheatsheet https://www.emmading.com/behavioral-interview-cheat-sheet ? Data Science Resume Checklist https://www.emmading.com/data-science-resume-checklist ✅ We work with Experienced Data Scientists to help them land their next dream jobs. Apply now: https://www.emmading.com/coaching // Comment Got any questions? Something to add? Write a comment below to chat. // Let's connect on LinkedIn: https://www.linkedin.com/in/emmading001/ ==================== Contents of this video: ==================== 0:00 Intro 1:27 Structure your answer for technical audience 2:08 Structure your answer for non-technical audience 3:04 Power, Type I error, Type II error (for technical audience) 5:15 Power, Type I error, Type II error (for non-technical audience) 6:17 Confidence interval (for technical audience) 8:33 Confidence interval (for non-technical audience) 9:20 P value (for technical audience) 11:29 P value (for non-technical audience)