New
Trending
SM
Clara Fargo
EBMT Clinical Research Quality Assurance Coordinator
I have finalised the demo for the ICH-GCP E6 R3 refresher course. Overall, I liked the content and the interface. I also want to thank Whitehall Train...
Biostatistics Learning Path
4.2
★★★★★
97% Recommended
Updated 2025
18 hours
118 active users
18 points
If you'd like to swap a course or add additional courses, Customize Your Bundle — or reach out to us and we'll tailor a learning path to your training needs.
Your Study Basket
1 x Biostatistics Learning Path
| Total | |
VAT is levied as per your country’s applicable rules and rates at checkout
Each course includes:
Fully compliant
This learning path covers essential biostatistical methods and practices used throughout clinical research, including statistical analysis, SAS and R programming, Statistical Analysis Plans, survival analysis, and sample size calculations. Learners develop practical knowledge that can be applied across clinical trial and drug development environments.
Certified
All learners who pass the final exam receive a uniquely numbered, personal certificate demonstrating their knowledge of biostatistics and its application in clinical research. Since questions are selected randomly from a database, re-sitting the exam provides a different assessment experience.
Affordable
Our cost-effective pricing provides excellent value compared with traditional classroom-based biostatistics training. Flexible learning options allow professionals to build statistical skills without the additional costs associated with face-to-face training, with group discounts available for larger purchases.
Time-saving
The online learning format allows professionals to complete biostatistics training at their own pace and choose when and where to study. Our administration system also makes it quick and simple to allocate licences to multiple learners and track their training progress.
Secure Payment Service
Rest assured we use secure processes to protect your payment.
Secured by:
About
The Biostatistics Learning Path prepares professionals to apply statistical principles and analytical methods throughout the clinical research and drug development lifecycle. It covers statistical methods for clinical research, SAS and R programming for clinical trials, Statistical Analysis Plans, survival analysis, and sample size calculations.
Participants will develop the skills to design statistically sound clinical studies, analyze and interpret clinical trial data, create robust statistical analysis plans, perform time-to-event analyses, determine appropriate sample sizes, and support scientifically rigorous and regulatory-compliant clinical research.
Courses Included
Applying R programming and statistical analysis techniques to clinical trial data management, analysis, visualization, and reporting.
3 hours
3 pointsApplying SAS programming techniques to clinical trial data management, statistical analysis, reporting, and regulatory-compliant clinical study outputs.
3 hours3 pointsApplying survival analysis methods to clinical trial data, including time-to-event outcomes, censoring, Kaplan–Meier analysis, and hazard models.
3 hours3 pointsDeveloping robust Statistical Analysis Plans that define clinical trial analyses, statistical methods, endpoints, datasets, and reporting requirements.
3 hours3 pointsApplying fundamental statistical methods to clinical research, including study design, data analysis, hypothesis testing, confidence intervals, and interpretation of clinical trial results.
3 hours3 pointsApplying statistical methods to determine appropriate sample sizes for clinical trials based on study design, power, significance levels, effect sizes, and variability.
3 hours3 pointsOur Certified Customers
Learner Rating & Reviews
4.7
★★★★★★
Average Rating
536 global ratings
★★★★★
87.0%
★★★★★
5.0%
★★★★★
3.0%
★★★★★
3.0%
★★★★★
2.0%
Frequently Asked Questions
- Biostatisticians and statistical programmers in clinical research
- Clinical research and clinical data management professionals
- Clinical trial statisticians and statistical analysis professionals
- SAS and R programmers supporting clinical trials
- Regulatory affairs and clinical development professionals involved in statistical reporting
- Researchers and professionals involved in clinical trial design and analysis
Upon completion of this learning path, participants will be able to apply core statistical methods to clinical research, perform clinical trial analyses using SAS and R, develop robust Statistical Analysis Plans, conduct survival and time-to-event analyses, determine appropriate clinical trial sample sizes, and interpret statistical results to support scientifically sound and regulatory-compliant clinical research.
Best Seller
