5 Statistics Concepts in Data Science Interviews | Power, Errors, Confidence Interval, P value
Top 5 Statistics Concepts in Data Science Interviews
In this video, we will talk about top 5 statistics concepts in data science interview. 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
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)
Видео 5 Statistics Concepts in Data Science Interviews | Power, Errors, Confidence Interval, P value канала Data Interview Pro
In this video, we will talk about top 5 statistics concepts in data science interview. 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
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)
Видео 5 Statistics Concepts in Data Science Interviews | Power, Errors, Confidence Interval, P value канала Data Interview Pro
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Cracking Hypothesis Testing Problems in Data Science Interviews | Binomial test, z-test and t-test
Cracking Metric/Business Case/Product Sense Problems | Data Science Interview
SQL Window Functions on Data Science Interviews in 2021 | Asked By Airbnb, Netflix, Twitter, Uber
3 Tips for Project-based Questions in Data Science interviews | How to Talk About Previous Projects
5 Types of Interviewers and How to Deal with Them | Data Science Interview
Facebook Data Scientist Mock Interview - Segment Influencers
What Happened During My Capital One TIP Interview
A/B Testing "Real-Life" Example: A Step by Step Walkthrough | Data Science Interview
Before Data Science Interview - 5 Guidelines
Sampling and Simulation Problems in Data Science Interviews | Simulate Fair Coin and Biased Coin
Facebook Product Manager Metrics Interview: Facebook Marketplace
What's in a Real SQL Interview | Data Science Interview
Cracking A/B Testing Problems in Data Science Interviews | Product Sense | Case Interview
Getting the First Data Scientist Job During the Pandemic | Real Talk with a Data Scientist
Facebook Product Manager Interview - Flawless Execution Interview Response by FB PM: Picking Metrics
How to Talk About Previous Data Science Projects in Interviews | Project-based Questions
LinkedIn Metric Interview Question and Answer | Data Science Interview | Decode and Conquer
LinkedIn Data Scientist Mock Interview + Feedback with Ex-DoorDash & Spotify Data Scientist!
Machine Learning Interview Questions and Answers | Machine Learning Interview Preparation | Edureka
Data Scientists Must Know: A/B Testing Fundamentals