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EOSA: Part 1

Provides learners with an introduction to foundational topics in statistics.

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About this Course


This eight-module course provides an introduction to statistical analysis. Moving from the basics of statistical thinking learners dive into a number of foundational topics including population and sample size, frequency distribution, and normal distribution. The course concludes with a review of skewness and kurtosis.

Language Availability: English

Suggested Audiences: IRB Members and Administrators, Undergraduate and Graduate Students, Research Faculty and Team Members, Clinical Research Coordinators

Organizational Subscription Price: $600 per year/per site (or included as part of the $1,250 annual subscription to the complete Essentials of Statistical Analysis course)
Independent Learner Price: $99 per person (or included as part of the $249 subscription to the complete Essentials of Statistical Analysis course)


Course Content


Introduction to Statistics

This module introduces the basics of statistical thinking. It establishes a foundation for the course.

Recommended Use: Required
ID (Language): 17609 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Population and Sample

This module reviews why and how samples are drawn from populations and introduces the concepts of sampling, representativeness, and statistical inferences.

Recommended Use: Required
ID (Language): 17610 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Central Tendency and Variability

This module introduces the tendency for scores to cluster around the “center” or “average,” and provides indices of the extent to which scores spread out from the center or average. Central tendency and variability are among the most fundamental concepts in statistics.

Recommended Use: Required
ID (Language): 17611 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Sensitivity and Specificity

This module introduces methods for determining the ability of diagnostic tests to correctly determine which cases do and do not meet specific criteria, as well as the ability of diagnostic tests to predict which cases will and will not meet criteria at some point in the future.

Recommended Use: Required
ID (Language): 17612 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Distribution and Probability

This module introduces the concept of frequency distributions, or shapes that data points create when they are plotted. The module also introduces various kinds of probability that are used in statistical reasoning and analyses.

Recommended Use: Required
ID (Language): 17613 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Probability and Odds

This module outlines the distinctions between probability and odds, and provides formulas for computing odds from probability and vice versa. The module also reviews statistics used for computing the associations between earlier events and later outcomes.

Recommended Use: Required
ID (Language): 17614 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Normal Distribution and Z-Scores

This module reviews the properties of the normal distribution, which underlies the family of analyses known as parametric tests. The module also introduces standard scores, which index how far a score is from the center of the dataset and can be used to compare the positions of a case’s scores across different variables.

Recommended Use: Required
ID (Language): 17615 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Skewness and Kurtosis

This module reviews statistical values that index the extent to which a variable’s frequency distribution departs from what would be expected under the normal distribution. These statistical values can be used to determine whether parametric statistics are appropriate for use with a given variable or set of variables.

Recommended Use: Required
ID (Language): 17616 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami