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Medical Statistics Courses

Medical statistics courses can help you learn data analysis techniques, study design principles, hypothesis testing, and the interpretation of clinical trial results. You can build skills in analyzing patient data, understanding epidemiological methods, and applying statistical software for real-world health problems. Many courses introduce tools like R, SAS, or SPSS, that support performing statistical analyses and visualizing health data effectively.


More to explore:

Popular Medical Statistics Courses and Certifications


  • Status: Preview
    Preview
    U

    University of Cape Town

    Understanding Clinical Research: Behind the Statistics

    Skills you'll gain: Biostatistics, Statistical Methods, Statistical Hypothesis Testing, Diagnostic Tests, Clinical Research, Statistical Analysis, Quantitative Research, Statistics, Descriptive Statistics, Statistical Inference, Data Collection, Probability

    4.8
    Rating, 4.8 out of 5 stars
    ·
    3.7K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Biostatistics in Public Health

    Skills you'll gain: Biostatistics, Statistical Hypothesis Testing, Logistic Regression, Regression Analysis, Sampling (Statistics), Statistical Methods, Statistical Visualization, Statistical Analysis, Epidemiology, Quantitative Research, Descriptive Statistics, Probability & Statistics, Statistical Inference, Probability Distribution, Scientific Methods, Public Health, Statistics, Statistical Modeling, Advanced Analytics, Predictive Modeling

    4.8
    Rating, 4.8 out of 5 stars
    ·
    2.4K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Preview
    Preview
    S

    Stanford University

    Introduction to Statistics

    Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.3K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Statistics for Data Science

    Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, Probability Distribution, R Programming, Biostatistics, Data Science, Statistics, Mathematical Modeling, Data Analysis, Data Modeling, Applied Mathematics

    4.4
    Rating, 4.4 out of 5 stars
    ·
    783 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Data Science: Statistics and Machine Learning

    Skills you'll gain: Shiny (R Package), Rmarkdown, Model Evaluation, Regression Analysis, Exploratory Data Analysis, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Machine Learning Algorithms, Plotly, Interactive Data Visualization, Probability & Statistics, Statistical Machine Learning, Data Presentation, Data Visualization, Statistical Analysis, Statistical Modeling, R Programming, Machine Learning, GitHub

    4.4
    Rating, 4.4 out of 5 stars
    ·
    7.2K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    M

    MedCerts

    Medical Billing and Coding Fundamentals

    Skills you'll gain: Medical Terminology, Revenue Cycle Management, Medical Billing, Medical Billing and Coding, Conflict Management, Anatomy, Pathology, Medical Coding, Cultural Responsiveness, Patient Education And Counseling, Patient-centered Care, Electronic Medical Record, Professionalism, Health Care Procedure and Regulation, Health Information Management and Medical Records, Professional Development, Medical Records, Time Management, Physiology, Payment Processing

    4.8
    Rating, 4.8 out of 5 stars
    ·
    1.7K reviews

    Beginner · Specialization · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    U

    University of Amsterdam

    Basic Statistics

    Skills you'll gain: Statistical Hypothesis Testing, Statistics, Scientific Methods, Quantitative Research, Data Analysis Software

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.6K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of California, Santa Cruz

    Bayesian Statistics

    Skills you'll gain: Bayesian Statistics, Time Series Analysis and Forecasting, Statistical Inference, Statistical Methods, R Programming, Forecasting, Probability & Statistics, Statistical Modeling, Technical Communication, Data Presentation, Probability, Statistics, Statistical Software, Probability Distribution, Statistical Analysis, Data Analysis, Markov Model, Model Evaluation, R (Software), Data Science

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.5K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    B

    Birla Institute of Technology & Science, Pilani

    Probability and Statistics

    Skills you'll gain: Data Analysis, Statistical Analysis, Data Visualization, Predictive Modeling, Applied Mathematics

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Inferential Statistics

    Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Statistical Reporting, R (Software), Statistical Methods, Statistics, R Programming, Statistical Analysis, Probability & Statistics, Data Analysis, Sampling (Statistics), Probability Distribution, Software Installation

    4.8
    Rating, 4.8 out of 5 stars
    ·
    2.8K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Statistics with Python

    Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Modeling, Statistical Methods, Statistical Inference, Bayesian Statistics, Data Visualization, Statistics, Matplotlib, Statistical Visualization, Statistical Software, Probability & Statistics, Model Evaluation, Statistical Analysis, Jupyter, Statistical Programming, Statistical Machine Learning, Regression Analysis, Data Visualization Software, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.3K reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: Preview
    Preview
    Y

    Yale University

    Understanding Medical Research: Your Facebook Friend is Wrong

    Skills you'll gain: Research Design, Medical Science and Research, Statistical Methods, Descriptive Statistics, Data Literacy, Scientific Methods, Clinical Research, Research, Biostatistics, Data Collection, Sampling (Statistics), Medical Terminology, Correlation Analysis

    4.9
    Rating, 4.9 out of 5 stars
    ·
    2.2K reviews

    Beginner · Course · 1 - 3 Months

1234…167

In summary, here are 10 of our most popular medical statistics courses

  • Understanding Clinical Research: Behind the Statistics: University of Cape Town
  • Biostatistics in Public Health: Johns Hopkins University
  • Introduction to Statistics: Stanford University
  • Advanced Statistics for Data Science: Johns Hopkins University
  • Data Science: Statistics and Machine Learning: Johns Hopkins University
  • Medical Billing and Coding Fundamentals: MedCerts
  • Basic Statistics: University of Amsterdam
  • Bayesian Statistics: University of California, Santa Cruz
  • Probability and Statistics: Birla Institute of Technology & Science, Pilani
  • Inferential Statistics: Duke University

Frequently Asked Questions about Medical Statistics

Medical statistics is a branch of statistics that focuses on the application of statistical methods to the field of medicine and public health. It plays a crucial role in designing studies, analyzing data, and interpreting results, which ultimately informs healthcare decisions and policies. Understanding medical statistics is important because it helps researchers and healthcare professionals evaluate the effectiveness of treatments, understand disease patterns, and make data-driven decisions that can improve patient outcomes.‎

A career in medical statistics can lead to various roles, including biostatistician, clinical data analyst, epidemiologist, and health informatics specialist. These positions often involve working with healthcare organizations, research institutions, or pharmaceutical companies to analyze data from clinical trials and public health studies. As the demand for data-driven decision-making in healthcare grows, opportunities in this field are expanding, making it a promising career choice for those interested in statistics and health.‎

To succeed in medical statistics, you should develop a strong foundation in statistical theory and methods, as well as proficiency in statistical software such as R, SAS, or Python. Key skills include data analysis, hypothesis testing, regression analysis, and an understanding of study design and epidemiology. Additionally, effective communication skills are essential for presenting findings to non-statistical audiences, ensuring that your insights can be understood and applied in real-world settings.‎

There are several online courses available that can help you learn medical statistics. Some recommended options include the Advanced Statistics for Data Science Specialization and the Statistics and Applied Data Analysis Specialization. These courses cover essential statistical concepts and techniques that are applicable in medical research and public health.‎

Yes. You can start learning medical statistics on Coursera for free in two ways:

  1. Preview the first module of many medical statistics courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in medical statistics, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn medical statistics, start by enrolling in foundational courses that cover basic statistical concepts and methods. Engage with practical examples and case studies to apply what you learn. Utilize online resources, such as webinars and forums, to enhance your understanding. Additionally, consider joining study groups or seeking mentorship from professionals in the field to gain insights and support as you progress.‎

Typical topics covered in medical statistics courses include descriptive statistics, probability theory, hypothesis testing, regression analysis, survival analysis, and clinical trial design. Courses may also explore specific applications of statistics in epidemiology, public health, and health policy, providing a comprehensive understanding of how statistical methods are applied in real-world medical contexts.‎

For training and upskilling employees in medical statistics, consider courses like the Data Science: Statistics and Machine Learning Specialization and the Foundations of Probability and Statistics Specialization. These programs are designed to equip professionals with the necessary skills to analyze healthcare data effectively and make informed decisions.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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