Scroll Down Arrow

EOSA: Part 2

Continues the exploration of statistical topics, expanding on the foundational points presented in Part 1.

ORGANIZATIONS

LEARNERS

Questions?

Contact Us


About this Course


This course continues the exploration of statistical analysis with a review of standard error and an introduction to type I/II errors. Also included are modules on confidence intervals, comparing two independent means, and paired samples T-tests.

Language Availability: English

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

Organizational Subscription Price: $500 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


Standard Error and Type I-II Errors

This module covers the standard error, an index of the amount of imprecision in a set of scores. The module also introduces two of the most common errors that can be committed when drawing conclusions from the results of statistical analyses.

Recommended Use: Required
ID (Language): 17617 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

The Four Horsemen

This module introduces four important factors that determine the results of statistical analyses. The module reviews the interrelationships among these factors and the process through which researchers can determine the number of cases needed when planning a study.

Recommended Use: Required
ID (Language): 17618 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Confidence Intervals and Degrees of Freedom

This module introduces confidence intervals, or ranges that are likely to contain the true value (such as average and correlation) that one wishes to determine. The module also reviews degrees of freedom – the number of values in a dataset that are free to vary – and how the degrees of freedom for an analysis affect the results of that analysis.

Recommended Use: Required
ID (Language): 17619 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Comparing Two Independent Means

This module reviews independent-samples t-tests, the most common parametric analyses used to compare scores from two groups with no members in common.

Recommended Use: Required
ID (Language): 17620 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Wilcoxon Rank-Sum Test

This module reviews the alternative to the independent-samples t-test when a parametric test cannot be used. Fundamentals of nonparametric tests are introduced.

Recommended Use: Required
ID (Language): 17622 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Paired Samples T-Test

This module reviews parametric methods for comparing two sets of scores drawn from the same group of cases.

Recommended Use: Required
ID (Language): 17623 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Nonparametric Methods for Paired Sample Data

This module covers the alternative to the paired-samples t-test when a parametric test cannot be used.

Recommended Use: Required
ID (Language): 17624 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami