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- Introduction to ProbabilityThe tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many fields, from the basic sciences to engineering and management.
- Introduction to Probability and StatisticsThis course provides an elementary introduction to probability and statistics with applications. Topics include: basic combinatorics, random variables, probability distributions, Bayesian inference, hypothesis testing, confidence intervals, and linear regression.
- Probabilistic Systems Analysis and Applied ProbabilityWelcome to 6.041/6.431, a subject on the modeling and analysis of random phenomena and processes, including the basics of statistical inference. Nowadays, there is broad consensus that the ability to think probabilistically is a fundamental component of scientific literacy.
- Statistical Thinking and Data AnalysisThis course is an introduction to statistical data analysis. Topics are chosen from applied probability, sampling, estimation, hypothesis testing, linear regression, analysis of variance, categorical data analysis, and nonparametric statistics.
- Statistics for ApplicationsThis course offers an in-depth the theoretical foundations for statistical methods that are useful in many applications. The goal is to understand the role of mathematics in the research and development of efficient statistical methods.
- Statistics Foundations 1Statistics is not just the realm of data scientists. All types of jobs use statistics. Statistics are important for making decisions, new discoveries, investments, and predictions. Whether the subject is political races, sports rankings, shopping trends, or healthcare advancements, statistics is an instrument for understanding your favorite topic at a deeper level. With these beginner-level lessons, you too can master the terms, formulas, and techniques needed to perform the most common types of statistics.
- Statistics Foundations 2Statistics are a core skill for many careers. Basic stats are critical for making decisions, new discoveries, investments, and even predictions. But sometimes you need to move beyond the basics. Statistics Fundamentals – Part 2 takes business users and data science mavens into practical, example-based learning of the intermediate skills associated with statistics: samples and sampling, confidence intervals, and hypothesis testing.
- Statistics Foundations 3Statistics are everywhere, in every industry, but they're a must for anyone working in data science, business, or business analytics. If you're in one of these specialized fields, chances are you need an advanced understanding of statistics. Complete your mastery in this course, part 3 of our Statistics Fundamentals series. Eddie Davila covers concepts such as small sample sizes, t-distribution, degrees of freedom, chi-square testing, and more. This advanced skills training moves learners into the practical study and application of experimental design, analysis of variance, population comparison, and regression analysis. Use these lessons to go beyond the basics and dive deeper into the specific factors that influence your own calculations and results.
- Statistics Foundations 4Statistics are everywhere, in every industry, but they're a must for anyone working in data science, business, or business analytics. If you're in one of these specialized fields, chances are you need an advanced understanding of statistics. Complete your mastery in this course, part four in our Statistics Foundations series. Eddie Davila covers concepts such as small sample sizes, t-distribution, degrees of freedom, and more. This advanced skills training moves learners into the practical study and application of experimental design, analysis of variance (ANOVA), two-population comparisons, and regression analysis. Use these lessons to go beyond the basics and dive deeper into the specific factors that influence your own calculations and results.
- Probability and Statistics: To p or not to p?In this course we consider many useful tools to deal with uncertainty and help us to make informed (and hence better) decisions - essential skills for a lifetime of good decision-making. Key topics include quantifying uncertainty with probability, descriptive statistics, point and interval estimation of means and proportions, the basics of hypothesis testing, and a selection of multivariate applications of key terms and concepts seen throughout the course.
- Basic StatisticsUnderstanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them.