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Statistics for Clinical Trials

Statistics for Clinical Trials is a "beyond" the basics statistical concepts program and it has direct applicability to clinical research. This online training program is designed for professionals having little or no formal training in math or statistics. Statistics for Clinical Trials is designed to teach the statistical principals for designing and analyzing clinical trials. This course covers such topics as the different types of study data, measuring variance, statistical concepts and tests, sample size calculation and interpretation of study results. The course will take approximately 25-30 hours to complete. You will have access to the course materials and instructor for questions for 60 days from the date of enrollment. A Certificate of Completion will be awarded at the end of the course.

Click HERE to view a demonstration version of Statistics for Clinical Trials.

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Who Should Attend

-CRAs/Monitors who will assist in the design and evaluation of studies.

-CRAs/Monitors who will be working with or communicating with statisticians.

-Clinical Project Leaders/Clinical Team Leaders who will assist in the design and evaluation of studies.

-Regulatory Professionals who use statistical concepts in their reports.

-Medical Writers who are involved in the interpretation of statistical reports.

Course Objectives

You will gain a firm understanding of the concepts and statistical methods used in clinical research. You will understand statistical terminology used in clinical research.You will understand how to interpret study results presented in clinical study tabulations, reports and scientific literature.


Instructions for use and Introduction

Types of Data

Quantitative Data

Qualitative Data

Descriptive Statistics


Measures of Central Tendency

-The Sample Mean

-The Sample Median

-The Sample Mode

-A look at measures of Central Tendency


Measures of Variability

-The Sample Variance

-The Sample Standard Deviation

-Other measures of variability

When do we use these statistics?

The Normal Distribution

Properties of the Normal Distribution

Parameters of the Normal Distribution

Standard Normal Distribution

Introduction to Statistical Inference

The Sampling Distribution

The Central Limit Theorem

Interval Estimation

Confidence Intervals


-The 95% confidence interval

-General form of the confidence interval

The t-distribution


-Properties of the t-distribution

-Using the t-distribution

-When to use the t-distribution

Two Sample Situations


-Two sample t-test

-Paired t-test

Hypothesis Testing


Steps to Hypothesis testing

Making Decisions and Conclusions


-Introduction to the p-value

-Interpreting the p-value

Testing our assumptions

-Testing the Normality Assumption

-Test for Equality of Variances

Hypothesis test and Confidence Intervals

Types of Error

Sample Size Calculations

Introduction to other Hypothesis Tests


Analysis of Variance

-Introduction to ANOVA

-One-way ANOVA

-Detecting the differences

-The Randomized Complete Block Design

The Chi-Square Test of Independence

Linear Regression

-Simple Linear Regression

-Multiple Linear Regressions


Concluding remarks