The Institute for Statistics Education at             Statistics.com

is the leading provider of online education in statistics.
We offer 100+ courses in introductory and advanced statistical subjects.
Students from around the world study with leading authorities via private discussion boards
on flexible schedules.
Teaching assistants provide individual responses in practical exercises.
Statistics.com confers CEU's, Records of Completion, and Certificates in advanced statistical study.

    Available courses

    Aim of Course:

    In this online course, "Programming 2:Python," you'll learn everything you need to get you started using Python for data analysis.  We'll review basic Python skills and data structures, move on to how to load data from different sources, rearrange and aggregate it, and finally how to analyze and visualize it to create high-quality products.

    Aim of Course:

    In this online course, "Programming 2:Python," you'll learn everything you need to get you started using Python for data analysis.  We'll review basic Python skills and data structures, move on to how to load data from different sources, rearrange and aggregate it, and finally how to analyze and visualize it to create high-quality products.

    Aim of Course:

    In this online course, "Programming 2:Python," you'll learn everything you need to get you started using Python for data analysis.  We'll review basic Python skills and data structures, move on to how to load data from different sources, rearrange and aggregate it, and finally how to analyze and visualize it to create high-quality products.

    Aim of Course:

    In this online course, "Programming 2:Python," you'll learn everything you need to get you started using Python for data analysis.  We'll review basic Python skills and data structures, move on to how to load data from different sources, rearrange and aggregate it, and finally how to analyze and visualize it to create high-quality products.

    Aim of Course:

    In this online course, "Programming 2:Python," you'll learn everything you need to get you started using Python for data analysis.  We'll review basic Python skills and data structures, move on to how to load data from different sources, rearrange and aggregate it, and finally how to analyze and visualize it to create high-quality products.

    Aim of Course:

    Continues the exploration of Rasch theory and its application in the Winsteps software, begun in "Practical Rasch Measurement-Core Topics." The course introduces exciting new topics and delves into earlier topics more deeply. Participants are encouraged to analyze their own datasets in parallel to the course datasets.

    Aim of Course:

    This course will show you how to use R to create statistical models and use them to analyze data.

    Aim of Course:

    Try out our introductory statistics series for one week - you can learn stats!

    Aim of Course:

    This course teaches participants how to model financial events that have uncertainties associated with them.

    Aim of Course:

    This course will introduce the essential techniques of text mining, understood here as the extension of data mining's standard predictive methods to unstructured text.

    Aim of Course:

    This course, the second in a three-course sequence, provides an easy introduction to inference and association through a series of practical applications, based on the resampling/simulation approach.

    Aim of Course:

    This course will teach you how to use various cluster analysis methods to identify possible clusters in multivariate data. In marketing applications, clusters of customer records are called market segments (and the process is called market segmentation).

    Aim of Course:

    This course will teach users how to implement spatial statistical analysis procedures using R software. Topics covered include point pattern analysis, identifying clusters, measures of spatial association, geographically weighted regression and surface processing.

    Aim of Course:

    To provide an easy introduction to statistical inference for a single variable.

    Aim of Course:

    Rasch analysis constructs linear measures from scored observations, such as responses to multiple-choice questions, Likert scales and quality-of-life assessments. This course covers the practical aspects of data setup, analysis, output interpretation, fit analysis, differential item functioning, dimensionality and reporting.

    Aim of Course:

    In this course you will work through a customer analytics project from beginning to end, using R.  You will start by gaining an understanding of the problem and the context, and continue to clean, prepare and explore the relevant data.

    In this course, you'll learn everything you need to get you started using Python for data analysis. - See more at: http://www.statistics.com/course-catalog/python/#syllabus

    Aim of Course:

    This course extends the Bayesian modeling framework to cover hierarchical models, and to add flexibility to standard Bayesian modeling problems.

    Aim of Course:

    In this course, you will learn how to make decisions in building a factor analysis model - including what model to use, the number of factors to retain, and the rotation method to use.

    Aim of Course:

    This course will introduce you to the basic concepts in predictive analytics, also called predictive modeling, the most prevalent form of data mining.

    Aim of Course:

    This course will introduce you to the basic concepts in predictive analytics, also called predictive modeling, the most prevalent form of data mining.