--- title: Statistics description: This subject introduces the fundamental concepts of collecting, analyzing, presenting, and interpreting data. Learners will understand basic probability, descriptive measures, and the foundational principles of statistical reasoning used to make data-driven decisions. category: programming-tech subcategory: data-science difficulty: beginner, intermediate, advanced url: /subject/introduction-to-statistics --- # Statistics This subject introduces the fundamental concepts of collecting, analyzing, presenting, and interpreting data. Learners will understand basic probability, descriptive measures, and the foundational principles of statistical reasoning used to make data-driven decisions. ## Available Resources 1 Videos • 7 Books • 4 Courses • 1 Websites ## Books ### 1. Introduction to Probability **Author:** Joseph K. Blitzstein, Jessica Hwang Learn the fundamentals of probability with this introductory book by Blitzstein & Hwang. Perfect for statistics beginners! **Difficulty:** Beginner | **Price:** Paid **Link:** https://www.amazon.com/dp/1466575573?tag=edmonddante07-20 **Tags:** probability, random-variables, probability-distributions, conditional-probability ### 2. Think Stats **Author:** Allen B. Downey Learn statistics with Python! Think Stats introduces probability and statistics concepts using real-world examples and computation. **Difficulty:** Beginner | **Price:** Paid **Link:** https://www.amazon.com/dp/1449307116?tag=edmonddante07-20 **Tags:** python, exploratory-data-analysis, probability, statistical-inference ### 3. OpenIntro Statistics **Author:** David Diez, Mine Cetinkaya-Rundel, Christopher Barr Learn statistics with OpenIntro Statistics! This free book covers introductory topics with clear explanations and examples. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.openintro.org/book/os/ **Tags:** introductory-statistics, hypothesis-testing, regression, open-textbook ### 4. Statistics for Business and Economics **Author:** Paul Newbold, William L. Carlson, Betty M. Thorne Mathematically rigorous business statistics textbook covering probability, sampling distributions, estimation, hypothesis testing, regression, and time series through applied business and economics problems. Readers learn to design and interpret statistical tests rather than simply run canned software procedures. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/0136085369?tag=edmonddante07-20 **Tags:** business-statistics, probability, hypothesis-testing, regression-analysis, statistical-inference ### 5. Naked Statistics **Author:** Charles Wheelan Popular-audience explanation of statistical reasoning without formulas, using cases from sports, medicine, and finance to show how correlation, regression, sampling, and probability get used and misused. Builds intuition rather than computational skill. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/039334777X?tag=edmonddante07-20 **Tags:** books, technology-computer-science, data-science--ai ### 6. Introduction to the Practice of Statistics **Author:** David S. Moore, George P. McCabe A data-first undergraduate statistics textbook covering exploratory data analysis, sampling and experimental design, probability, and inference. Working through it, you can design a study, choose an appropriate test, and interpret confidence intervals and p-values correctly. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/071672250X?tag=edmonddante07-20 **Tags:** statistics, statistical-inference, hypothesis-testing, exploratory-data-analysis, experimental-design ### 7. Statistics **Author:** David Freedman, Robert Pisani, Roger Purves Classic introductory textbook that teaches statistical reasoning through experimental design, observational studies, and real case histories, with careful treatment of chance, sampling, and regression. Emphasizes interpreting studies correctly over formula manipulation. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/0393970833?tag=edmonddante07-20 **Tags:** books, technology-computer-science, data-science--ai ## Videos ### 1. Statistics Fundamentals Josh Starmer's video series explaining core statistical ideas, distributions, sampling, p-values, confidence intervals, hypothesis tests, and regression, with hand-drawn visuals and worked examples. After watching, you can interpret common statistical output in data science work. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.youtube.com/playlist?list=PLblh5JKOoLUK0FLuzwntyYI10UQFUhsY9 **Tags:** statistics-fundamentals, p-values, confidence-intervals, regression, data-science ## Courses ### 1. Statistics 110: Probability Learn probability fundamentals with Harvard's Statistics 110 course, taught by Joe Blitzstein. Perfect for building a strong statistical foundation! **Difficulty:** Beginner | **Price:** Free **Link:** https://www.youtube.com/playlist?list=PL2SOU6wwxB0uwwH80KTQ6ht66KWxbzTIo **Tags:** probability, conditional-probability, random-variables, markov-chains ### 2. Statistics Learn statistics fundamentals with this free course from Khan Academy! Master probability, data analysis, and more. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.khanacademy.org/math/statistics-probability **Tags:** introductory-statistics, probability, data-analysis, hypothesis-testing ### 3. Statistics with Python University of Wisconsin-Madison course on edX covering descriptive statistics, probability, inference, correlation, and regression, taught with Python. You finish able to summarize data, quantify uncertainty in estimates, and fit and interpret regression models. **Difficulty:** Beginner | **Language:** English | **Price:** Free **Link:** https://www.edx.org/learn/statistics/the-university-of-wisconsin-madison-statistics-using-python **Tags:** courses, technology-computer-science, data-science--ai ### 4. Introduction to Statistics Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You will gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning. Topics include Descriptive Statistics, Sampling and Randomized Controlled Experiments, Probability, Sampling Distributions and the Central Limit Theorem, Regression, Common Tests of Significance, Resampling, Multiple Comparisons. **Difficulty:** Beginner | **Language:** English | **Duration:** This course will take approx. 6-8 hours to complete, depending on prior knowledge and experience. | **Price:** Free **Link:** https://www.coursera.org/learn/stanford-statistics **Tags:** courses, mathematics-statistics, statistics-and-probability ## Youtubes ### 1. StatQuest with Josh Starmer **Author:** Josh Starmer YouTube channel by Josh Starmer that explains statistics and machine learning step by step, from p-values, linear models and ANOVA to PCA, decision trees, neural networks and transformers. Viewers build clear intuition for how common methods work before tackling the math. **Difficulty:** Beginner | **Language:** English | **Price:** Free **Link:** https://www.youtube.com/@statquest **Tags:** statistics, machine-learning, statistical-intuition, data-analysis ## Websites ### 1. seeing-theory.brown.edu Seeing Theory is an interactive, browser-based resource from Brown University that uses visual simulations to explain fundamental probability and statistics concepts. It offers interactive demos and explanations on topics like probability, distributions, sampling, the central limit theorem, confidence intervals, hypothesis testing, and Bayesian reasoning. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://seeing-theory.brown.edu **Tags:** websites, technology-computer-science, data-science--ai --- *This content is part of Dantes.io - Your Treasure Map to Knowledge* *Curated by humans at Dantes.io. Personal study use welcome; republishing this curation requires permission (team@dantes.io).* View this page online: https://dantes.io/subject/introduction-to-statistics