Statistics: A Step-by-step Introduction

📚 Introduction to Statistics for Data Science

🚀 Course Headline: Lessons and examples from a former Google data scientist to master hypothesis tests, confidence intervals, and more!

🌍 About the Instructor: Brian Grecot is a seasoned data scientist with years of experience at Google. His expertise in statistics and data analysis has led to groundbreaking projects that have shaped how we understand and utilize data science. Now, he's bringing his knowledge straight to you in this comprehensive course designed for both beginners and professionals alike.

🔍 Course Description: Dive into the world of statistics with our "Introduction to Statistics for Data Science" course. This program is tailored to provide a solid foundation in statistics, focusing on hypothesis testing for proportions, means, and categorical data - essential skills for any data scientist. With over 10 hours of video lectures, innovative lightboard technology makes learning engaging and interactive.

Key Features:

• Video Lectures: 📹 10 hours of face-to-face instruction using cutting-edge lightboard technology to enhance your learning experience.
• Supplementary Notes: 📓 Detailed lecture notes accompany each lesson, reinforcing key concepts with vocabulary, examples, and explanations.
• Quizzes & Assignments: ✅ 19 quizzes to test your knowledge and 9 assignments, complete with solutions, to solidify your understanding.

Course Highlights:

• Common Terminology & Graphs: Learn the language of data and familiarize yourself with essential graphs used in statistics.
• Basic Probability: Get a grip on random variables, probability mass functions, cumulative distribution functions, and the binomial distribution.
• Normal Distribution & Z-scores: Understand the significance of the normal distribution, z-scores, and how to use z-tables for probability calculations.
• Hypothesis Testing: Master the concepts of Type I errors, alpha, critical values, and p-values. Learn to conduct hypothesis tests using z-tests and t-tests for proportions and means.
• Confidence Intervals: Discover how confidence intervals are constructed and the relationship between these and hypothesis testing.
• Chi-square Tests: Conduct goodness-of-fit, homogeneity, and independence tests with a chi-square test.
• Correlation & Linear Regression: Get an introduction to correlation and simple linear regression, setting the stage for more advanced statistical modeling.

This course is your gateway to mastering statistics in data science, suitable for:

• Aspiring Statisticians: Anyone looking to learn the foundations of statistics and understand concepts like p-values and confidence intervals.
• Students: Ideal for those taking an introductory college or high school statistics class who want additional explanations and detailed examples.
• Data Science Professionals: Perfect for professionals refreshing their knowledge or expanding it in preparation for job interviews.

🎓 Who Should Take This Course? This course is designed for a wide range of students, from those just starting out with statistics to seasoned data science professionals. Whether you're looking to satisfy course requirements, enhance your skill set, or prepare for an exciting career in data science, this course offers the comprehensive instruction you need.

Join Brian Grecot and embark on a journey through the core concepts of statistics, equipping yourself with the tools to interpret data confidently and make informed decisions based on statistical evidence. 📊✨