Essentials of Statistical Analysis (EOSA): Part 3

Completes the overview of statistical topics, including advanced and often challenging analyses.

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About this Course


In this eleven-module course, advanced statistical topics are covered. The course begins with an overview of parametric methods used to compare scores across three or more groups. Other topics include ANOVAs, correlations, and multiple regression.

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Language Availability: English

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

Organizational Subscription Price: $400 per year/per site or included as part of the $1,250 annual subscription to EOSA: Complete
Independent Learner Price: $99 per person or included as part of the $249 subscription to EOSA: Complete

Demo Instructions

Course Content


Analysis of Variance

This module covers parametric methods used to compare scores across three or more groups.

Recommended Use: Required
ID (Language): 17625 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Following Up a Significant ANOVA

This module introduces methods that can be used to determine, following a significant overall result, which groups are significantly different from the other groups on the variable being compared.

Recommended Use: Required
ID (Language): 17626 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Kruskal-Wallis One-Way ANOVA

This module reviews the alternative to the analyses of variance when parametric analyses cannot be used.

Recommended Use: Required
ID (Language): 17627 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Proportions

This module introduces proportions, or percentages of cases that meet a specified set of criteria. The module also reviews fundamental concepts involved in analyzing and comparing proportions.

Recommended Use: Required
ID (Language): 17628 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Comparing Two Independent Proportions

This module reviews methods for comparing proportions across groups that do not share members in common.

Recommended Use: Required
ID (Language): 17629 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Contingency Tables and Chi-Square Tests

This module introduces methods for analyzing the relationship between two categorical variables, and for identifying the specific categories that are most responsible for the relationship.

Recommended Use: Required
ID (Language): 17630 (English)

Other Contingency Table Analyses

This module reviews methods for comparing categories within a single categorical variable, and for comparing two proportions from the same set of cases.

Recommended Use: Required
ID (Language): 17631 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Correlations

This module reviews parametric and nonparametric methods for determining the strength of association between two sets of numerical scores.

Recommended Use: Required
ID (Language): 17632 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Comparing Correlation Coefficients

This module reviews methods for comparing associations across different groups of cases and within a single group of cases.

Recommended Use: Required
ID (Language): 17633 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Simple Linear Regression

This module covers different types of predictive relationships and reviews methods for determining the relationship between a predictor and an outcome.

Recommended Use: Required
ID (Language): 17634 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami

Multiple Regression

This module reviews methods for examining the relationships of multiple predictors to a single outcome variable.

Recommended Use: Required
ID (Language): 17635 (English)
Author(s): Seth J. Schwartz, PhD - University of Miami


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