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Introduction to Statistics for Data Science - BaDshaH - 11-27-2024
![[Image: 703060b840bbd80b1df26ae13cf4a450.jpg]](https://i124.fastpic.org/big/2024/1127/50/703060b840bbd80b1df26ae13cf4a450.jpg)
Last updated 10/2024
Created by Brian Greco
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 79 Lectures ( 10h 4m ) | Size: 5.6 GB
Lessons and examples from a former Google data scientist to master hypothesis tests, confidence intervals, and more
What you'll learn
Build a strong statistical vocabulary and foundation in probability
Learn to tests hypotheses for proportions and means
Learn how to create confidence intervals, and their connection to hypothesis tests
Learn how to perform chi-square tests for categorical data
Requirements
Basic arithmetic skills
Basic algebra (ability to understand equations with variables)
Description
This course teaches the foundational material of statistics covered in an introductory college course, with a focus on mastering hypothesis testing for proportions, means, and categorical data.The course includes:10 hours of video lectures, using the innovative lightboard technology to deliver face-to-face lecturesSupplementary lecture notes with each lesson covering important vocabulary, examples and explanations from the video lessons19 quizzes to check your understanding9 assignments with solutions to practice what you have learnedYou will learn about:Common terminology to describe different types of data and learn about commonly used graphsBasic probability, including the concept of a random variable, probability mass functions, cumulative distribution functions, and the binomial distributionWhat is the normal distribution, why it is so important, and how to use z-scores and z-tables to compute probabilitiesType I errors, alpha, critical values, and p-valuesHow to conduct hypothesis tests for one and two proportions using a z-testHow to conduct hypothesis tests for one and two means using a t-testConfidence Intervals for proportions and means, and the connection between hypothesis testing and confidence intervalsHow to conduct a chi-square goodness-of-fit testHow to conduct a chi-square test of homogeneity and independence.An introduction to correlation and simple linear regressionThis course is ideal for many types of students:Anyone who wants to learn the foundations of statistics and understand concepts like p-values and confidence intervalsStudents taking an introductory college or high school statistics class who would like further explanations and detailed examplesData science professionals who would like to refresh and expand their statistics knowledge to prepare for job interviews
Who this course is for
Self-learners who want a strong college-level foundational course in statistics
College and high school students who need to supplement their course with high-quality lectures and example problems
Data science professionals looking to refresh or expand their knowledge to prepare for job interviews
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