Statistics: A Step-by-step Introduction
Master the foundations of statistics with this comprehensive course. Learn hypothesis testing, confidence intervals, and chi-square tests for data analysis. Ideal for students and data science professionals seeking a strong statistical vocabulary and a solid understanding of key concepts.
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
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 lectures
Supplementary lecture notes with each lesson covering important vocabulary, examples and explanations from the video lessons
19 quizzes to check your understanding
9 assignments with solutions to practice what you have learned
You will learn about:
Common terminology to describe different types of data and learn about commonly used graphs
Basic probability, including the concept of a random variable, probability mass functions, cumulative distribution functions, and the binomial distribution
What is the normal distribution, why it is so important, and how to use z-scores and z-tables to compute probabilities
Type I errors, alpha, critical values, and p-values
How to conduct hypothesis tests for one and two proportions using a z-test
How to conduct hypothesis tests for one and two means using a t-test
Confidence Intervals for proportions and means, and the connection between hypothesis testing and confidence intervals
How to conduct a chi-square goodness-of-fit test
How to conduct a chi-square test of homogeneity and independence.
An introduction to correlation and simple linear regression
This 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 intervals
Students taking an introductory college or high school statistics class who would like further explanations and detailed examples
Data 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
