Biostatistics for Credit
Biostatistics for Credit reviews the procedures covered in the introductory courses Biostatistics 1 and Biostatistics 2, and covers in more detail the principal statistical concepts used in medical and health sciences.
Overview
This is an eight-week, non-mathematical course designed specifically for medical and health professionals who deal with medical data and want to acquire some statistical skills. It is a two-part course that may be taken together for college credit.
Part 1 covers basic statistical concepts of probability, confidence intervals and medical vs. statistical significance.
Part 2 covers clinical trial designs including randomized controlled trials, ROC curves, relative risk and odds ratios, and an introduction to survival analysis.
- Intermediate
- 8 Weeks
- Expert Instructor
- Tuiton-Back Guarantee
- 100% Online
- TA Support
Learning Outcomes
Students who complete this two-part, eight-week course will be able to explain the role of probability in health and medicine; calculate confidence intervals; describe the differences between statistical and medical significance; select the proper statistical tests for quantitative data; be familiar with designs for clinical trials; plot ROC curves; calculate relative risk (RR) and odds ratio (OR); and understand introductory survival analysis.
- Apply Bayes Rule to diagnostic tests
- Calculate the sensitivity, specificity, and positive/negative predictive value of a medical test
- Calculate large-sample and exact confidence intervals for means, medians and proportions
- Calculate and explain p-values
- Explain the concept of statistical power
- Perform the chi-square test
- Apply Student’s t-test to one- and two-sample situations
- Conduct an ANOVA test
- Apply the Tukey and Bonferroni corrections for multiple comparisons
- Test for bioequivalence
- Specify the design for a basic clinical trial, with randomization, blinding, masking and a control group
- Explain designs for repeated measures and cross-over trials
- Determine and interpret ROC curves
- Calculate relative risk and odds ratios and their confidence intervals
- Conduct inference procedures for relative risk and odds ratios
- Explain and apply basic survival analysis models (censoring, Kaplan-Meier)
Who Should Take This Course
This non-mathematical course is specially designed for medical and health professionals who deal with medical data and want to acquire some statistical skills. These include nursing, pharmacy, laboratory technology and nutrition professionals beside physicians, surgeons and dentists.
Our Instructors
Dr. Abhaya Indrayan
Dr Abhaya Indrayan is the former Professor and Chair of the Department of Biostatistics and
Medical Informatics at Delhi University College of Medical Sciences, Delhi, and is the author of
several books, including Medical Biostatistics (4th ed. CRC Press). Currently working as
Biostatistics Consultant at Max Healthcare Institute, New Delhi, he has frequently provided
biostatistical consultation to the World Health Organization, the World Bank, and UNAIDS. He
completed his M.S. and Ph.D. from the Ohio State University. Prof Indrayan has been a Visiting
Faculty at the Ohio State University and a Visiting Scientist at the University of Massachusetts.
He is an elected Fellow of several academic bodies and a recipient of several awards.
Course Syllabus
Week 1
Probability in Health and Medicine
- Medical uncertainties and probability
- Elementary laws of probability
- Bayes’ Rule
- Sensitivity-specificity of a medical test
- Positive and negative predictive value
- Effect of prevalence
Week 2
Confidence Intervals
- Sampling distributions and SEs
- Large sample CI for one-sample mean and proportion
- Exact CI for proportion and median
- Large sample CI for differences between means and proportions
- Sample size for estimation
Week 3
Statistical vs. Medical Significance
- P-value and level of significance
- The concept of statistical power
- Medical vs. statistical significance
- Sample size for significance and power analysis
- Chi-square test for simple situations
Week 4
Some Statistical Tests for Quantitative Data
- Student’s t-test for one-sample and two-sample situations
- ANOVA for one-way and two-way tables
- Tukey test and Bonferroni procedures for multiple comparisons
- Test for medically significant gain and equivalence test
Week 5
Introduction to Designs for Clinical Trials
- Control group
- Randomization and matching
- Blinding and masking
- One-way, two-way and repeated measures designs
- Cross-over design
Week 6
ROC Curves
- Review of sensitivity-specificity
- Serial and parallel tests
- ROC curve
- Predictivity-based ROC curve
- Clinical gains from a test
Week 7
Relative Risk (RR) and Odds Ratio (OR)
- Definitions and applicability of RR and OR
- CI and test of hypothesis for RR
- CI and test of hypothesis for attributable risk
- CI and test of hypothesis for OR
Week 8
Introductory Survival Analysis
- Censored durations and need of special methods
- Life table method
- Kaplan-Meier method
Class Dates
2025
Instructors: Dr. Abhaya Indrayan
Instructors: Dr. Abhaya Indrayan
Prerequisites
There are no prerequisites for this course.
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Additional Information
Organization of Course
This course is comprised of two separate courses, taken together for college credit. Note: Parts 1 and 2 can be taken separately.
- Part 1: Biostatistics 1 (4 weeks)
- Part 2: Biostatistics 2 (4 weeks)
Time Requirements
About 15 hours per week, at times of your choosing.
Course Text
The course text is Medical Biostatistics, fourth ed., by Abhaya Indrayan, and can be ordered directly from the publisher, CRC Press.
Software
Course participants should have access to a standard statistical software package for use in course exercises, including obtaining CI’s, performing tests of significance including two-way ANOVA and multiple comparisons tests, and producing ROC curves. Stata, SAS, MedCalc and R have these capabilities and are supported by statistics.com teaching assistants. SPSS and Systat also have these capabilities.
Options for Credit and Recognition
ACE CREDIT | College Credit
This course has been evaluated by the American Council on Education (ACE) and is recommended for the upper-division baccalaureate degree, 3 semester hours in biostatistics. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.
Supplemental Information
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