Essentials of Statistical Analysis (EOSA)

Covers the essentials of statistical analysis to help learners gain greater statistical literacy.

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About this Course

Designed for researchers, research personnel, coordinators, administrators, postdocs, and students, the Essentials of Statistical Analysis (EOSA) course aims to build your statistical literacy and enhance your research capabilities.

The course covers key concepts in statistical analysis, including populations and samples, central tendency and variability, distributions and probability, normal distributions and z-scores, skewness and kurtosis, standard error and errors in hypothesis testing, statistical power and sample size estimation, confidence intervals and degrees of freedom, analysis of variance, correlation, multiple linear regression, t-tests, simple linear regression, non-parametric tests, contingency table measures, and diagnostic accuracy.

Language Availability: English

Suggested Audiences: Postdocs, Research Administrators, Research Coordinators, Research Personnel, Researchers, Students

Organizational Subscription Price: $1,620 per year/per site for government and non-profit organizations; $1,800 per year/per site for for-profit organizations
Independent Learner Price: $249 per person

Demo Instructions


Course Content

Introduction to Statistics

Provides an introduction to the EOSA course. This module also examines the role of statistical analyses within the research process, the importance of planning before conducting a study, random variables, and the levels of scaling.

Recommended Use: Required
ID (Language): 21444 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Populations and Samples

Explains the difference between a population and a sample, why samples are used instead of entire populations, and different types of sampling procedures.

Recommended Use: Required
ID (Language): 21445 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Central Tendency and Variability

Describes the importance of central tendency in statistical analyses, different types of central tendency (mean, median, and mode), the importance of variability within the context of data analysis, and when certain measures of central tendency and variability should be used.

Recommended Use: Required
ID (Language): 21446 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Distributions and Probability

Explains plots that help understand the shape of a distribution, how to identify and interpret the skewness of a distribution, statistical tests that check the assumption of normality, and how the normal distribution is used as the basis for many statistical tests.

Recommended Use: Required
ID (Language): 21447 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Normal Distribution and Z-Scores

Examines the properties of the normal distribution, why the normal distribution is used for many statistical analyses, what a z-score is and how to calculate it, and how standard scores are used in clinical and research applications.

Recommended Use: Required
ID (Language): 21448 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Skewness and Kurtosis

Describes skewness and kurtosis, skewness and kurtosis values, and how transformations can be applied to skewed data to better approximate a normal distribution.

Recommended Use: Required
ID (Language): 21449 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Standard Error and Type I and Type II Errors

Defines the concept of standard error, null and alternative hypotheses, and Type I and Type II errors.

Recommended Use: Required
ID (Language): 21450 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Statistical Power and Sample Size Estimation

Explains how significance level, sample size, standard deviation, and statistical power determine the results of statistical tests. The module also explains how effect size, standard deviation, and statistical power are used to calculate the necessary sample size for a study.

Recommended Use: Required
ID (Language): 21451 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Confidence Intervals and Degrees of Freedom

Describes how confidence intervals are used to assess the precision of an estimate, the mechanics of how confidence intervals are derived, and degrees of freedom.

Recommended Use: Required
ID (Language): 21452 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Correlation

Explains how correlations are used to assess associations between two continuous or rank-order variables, how to interpret the direction and strength of correlation values, and the Pearson and Spearman correlations.

Recommended Use: Required
ID (Language): 21453 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Simple Linear Regression

Discusses how linear regression is used to make predictions, what residual values are and why they are important, how model fit is assessed, and how to distinguish between confidence intervals and confidence bands.

Recommended Use: Required
ID (Language): 21454 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Multiple Linear Regression

Describes how multiple linear regression differs from simple linear regression, how variables in a regression model serve as covariates, how covariates are selected to be included in a regression model, and how to use and interpret model fit statistics to determine if the addition of variables to a model improves its predictive power.

Recommended Use: Required
ID (Language): 21455 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

T-Tests

Identifies the differences between the one-sample, two-sample, and paired-samples t-tests. The module also describes the different research study designs in which each of the t-tests are used and how to correctly interpret Cohen’s d effect size values.

Recommended Use: Required
ID (Language): 21456 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Analysis of Variance (ANOVA)

Identifies the differences between the one-way, two-way, and repeated measures ANOVA. The module also examines when each ANOVA should be used based on the study design and the partial eta-squared effect size used for ANOVAs.

Recommended Use: Required
ID (Language): 21457 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Non-Parametric Tests

Examines non-parametric tests and situations in which non-parametric tests should be used to analyze data.

Recommended Use: Required
ID (Language): 21458 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Contingency Table Measures

Describes the chi-square test, the McNemar test, relative risk and the odds ratio, the number needed to treat, and the kappa statistic.

Recommended Use: Required
ID (Language): 21459 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute

Diagnostic Accuracy

Explains sensitivity and specificity, positive and negative predictive values, and area under the curve.

Recommended Use: Required
ID (Language): 21460 (English)
Author(s): Michael Malek-Ahmadi, PhD - Banner Alzheimer’s Institute


FAQs

Who should take the Essentials of Statistical Analysis course?

The Essentials of Statistical Analysis course is for researchers, research personnel, research coordinators and administrators, postdocs, and students. It would be meaningful to anyone interested in gaining greater statistical literacy.

How long does it take to complete the Essentials of Statistical Analysis course?

Each module is designed to take about 5 to 15 minutes. The entire course is designed to take about three hours complete.

What are the standard recommendations for learner groups?

This course is designed such that learners should complete all modules in sequence.

Is this course eligible for continuing medical education credits?

This course does not currently have CE/CME credits available.

Does this course replace CITI Program’s previous Essentials of Statistical Analysis courses?

Yes, this course serves as an updated version of CITI Program’s EOSA Complete, EOSA Part 1, EOSA Part 2, and EOSA Part 3 courses. For more information on this update, see “Update to Essentials of Statistical Analysis (EOSA) Content."


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