NEW COURSE - Statistics for Clinical Research
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NEW COURSE - Statistics for Clinical Research


Course Description

This is a "beyond" a basic 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 Research 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.

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.





Statistics for Clinical Research


  1. Instructions for use and Introduction
  2. Types of Data
    1. Quantitative Data
    2. Qualitative Data
  3. Descriptive Statistics
    1. Introduction
    2. Measures of Central Tendency

                        -The Sample Mean

-The Sample Median

-The Sample Mode

-A look at measures of Central Tendency

    1. Percentiles
    2. Measures of Variability

  -The Sample Variance

  -The Sample Standard Deviation

  -Other measures of variability

E. When do we use these statistics?


  1. The Normal Distribution
    1. Properties of the Normal Distribution
    2. Parameters of the Normal Distribution
    3. Standard Normal Distribution


5. Introduction to Statistical Inference

    1. The Sampling Distribution
    2. The Central Limit Theorem


6.Interval Estimation

    1. Confidence Intervals


-The 95% confidence interval

-General form of the confidence interval

    1. The t-distribution


-Properties of the t-distribution

-Using the t-distribution

-When to use the t-distribution

    1. Two Sample Situations


-Two sample t-test

-Paired t-test 



  1. Hypothesis Testing
    1. Introduction
    2. Steps to Hypothesis testing
    3. Making Decisions and Conclusions


-Introduction to the p-value

-Interpreting the p-value

    1. Testing our assumptions

-Testing the Normality Assumption

-Test for Equality of Variances

    1. Hypothesis test and Confidence Intervals
    2. Types of Error
    3. Sample Size Calculations


   8. Introduction to other Hypothesis Tests

    1. Introduction
    2. Analysis of Variance

-Introduction to ANOVA

-One-way ANOVA       

-Detecting the differences

-The Randomized Complete Block Design

    1. The Chi-Square Test of Independence
    2. Linear Regression

  -Simple Linear Regression

  -Multiple Linear Regressions


  1. Concluding remarks