Introduction

Clinical trial managers are now working closely with other groups within a clinical trial to ensure that data is collected, managed, and reported in a timely manner, accurately, and securely. Therefore the clinical trial manager must understand good clinical practices, protocol, protocol deviations, metadata, basic SDTM mapping, programming, and Excel. Therefore building the skills of clinical trial managers is essential.

Course Outcome

After the course, participants should be able to:

• Describe various type of data and  how they are used
• Describe confidence interval and p-values
• Describe how to identify information to perform basic sample size calculation
• Describe and interpret simple analysis
• Define correlation and simpler linear regression
• Understand the value and opportunities of data
• Describe randomisation, blocking and power calculations

Course Module

• Normal Distribution
•        Basic Study design
•       Confidence Interval
•        Basic concepts in probability
•        Introduction to hypothesis test
•        Analysis of Contingency tables
•        T-test, non-parametric tests
•        Correlation and regression
•        Introduction to data science and results
•        Using Excel for Statistical & Data Analysis
•        Data integrity and statistical inference
•        Getting started with R
•        Study design: randomisation and blocking
•       Study design: power calculation
•    Method comparison & Reproducibility studies

Teaching: The course will be taught through series of online tutorials, online formative exercises, series of pod-casts and discussion forums. It is compulsory that student take part in 90% of online tutorials.  Self-directed learning is an essential component of this training. Electronic learning resources will be made available via our VLE.

Learning breakdown: Our online courses combine several elements to create a balanced blend of learning. Learners will be able to learn at their own pace during the week by viewing content, engaged in discussions, and completing assignments. It is expected that on the average, 8 to 10 hours per week is required for a course.

Assessment:  Assessment for this course is based on summative assessment which counts to the module mark. Each summative assessment for a module will be made of a 1000 word essays, scientific article of high standard, 15 minutes presentations, and 3000 worded final assignment.

Commitment: 8-10 hours per week as follows:

Eligibility: The course is designed for clinical trial manager who want to improve their skills and understanding of statistics applied to clinical trials.