Biostatistics online courses is studying and applying statistical reasoning and methodology in public health, healthcare, and biomedical, clinical, and population-based science. According to the Oxford Journal of Life Sciences, Mathematics and Physical Science, Biostatistics is a discipline whose primary aim is “to advance statistical science and its application to problems of human health and disease, with the ultimate goal of advancing the public’s health.”
We compiled the list of the best biostatistics online courses for you, which helps you to get knowledge in the biostatistics field. It includes both paid and free resources to help you learn Biostatistics, and these courses are suitable for beginners, intermediate learners, and experts. The list covers the details of courses, the duration of the courses, and the direct link to enroll now.
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Biostatisticians work with various organizations, including hospitals, government departments, colleges, and even private businesses. To protect the public, they are in charge of controlling disease transmission and causes of death. Biostatistics is a multibillion-dollar market that is critical to improving human health and understanding public health problems. The government and the pharmaceutical industry primarily support the biostatistics industry. Between 2018 – 28, the Bureau of Labor Statistics expects a 30 percent increase in work opportunities for all categories of statisticians, including biostatisticians.
Future biostatisticians will work as data analysts to strengthen their numerical skills. Individuals may begin as research assistants to gain firsthand experience with laboratory protocols. Young quantitative scientists may be able to find mentors in the form of principal investigators.
Biostatistics is a well-respected and well-paid area of research. People with a suitable skill set can pursue a rewarding and essential career. A career as a Biostatistician is an excellent way to combine your interests in mathematics, science, statistics, and health.
This course designs to serve as a refresher. Students will complete a collaborative, real-life project demonstrating their comprehension of the techniques and applications discussed in the course, including descriptive and inferential statistics.
Topics include:
Provider: UC San Diego
Subject: Biostatistics
Duration: Self-paced
Start Date: Open
This Specialization designs public health and healthcare practitioners, academics, data analysts, social workers, and others who need a detailed biostatistics primer focused on concepts. Those who complete the Specialization will read and react to scientific literature in public health, medicine, biological science, and related fields, including the Methods and Results pages. Learners who succeed will also be prepared to work as part of a research team.
Provider: Johns Hopkins University
Subject: Biostatistics
Duration: 4 months
Start Date: Open
The course created by Dr. Juan Klopper, the head of the Acute Care Surgery division of the Department of Surgery in the Health Sciences Faculty, and aimed at health practitioners who must interpret clinical research statistics in published research.
This course is an excellent place to start if you want to learn how to read the literature correctly or if you want to do your study. It provides a simple way to understand basic statistical concepts without getting bogged down in mathematical formulae. The best way to begin your journey into the field of clinical literature is to be able to perceive and comprehend these concepts. It is where this course will help, so let’s get started!
Provider: University of Cape Town
Subject: Biostatistics
Duration: 27 hours
Start Date: Open
This course has a single, straightforward goal: to teach you how to conduct statistical tests that you can use in your dissertations, research papers, and presentations. The ability to summarise data, generate plots and charts, and perform the tests commonly seen in the literature is a particular skill. It will advance your career and allow you to contribute to humanity’s development through scientific research.
This course adheres to the current trend in studying statistical analysis using a programming language. It does not necessitate any previous coding experience. A thrilling journey lies ahead. If you want to learn even more, optional Honors machine learning lessons cover the Wolfram Language’s support for deep learning.
Provider: University of Cape Town
Subject: Biostatistics
Duration: 15 hours
Start Date: Open
The principles and methods required to comprehend, analyze, and interpret data from next-generation sequencing experiments to cover this Specialization. It teaches how to use the command line and software implementation techniques such as Python, R, Bioconductor, and Galaxy and how to use the command line in genomic data science.
This Specialization intended to serve as a standalone introduction to genomic data science or as a perfect complement to a primary degree or postdoc in biology, molecular biology, or genetics for scientists in these fields who want to gain familiarity with data science and statistical methods to better engage with data in their daily work.
Provider: Johns Hopkins University with The Institution For Data Intensive Engineering And Science
Subject: Biostatistics
Duration: 10 months
Start Date: Open
The application of statistical expertise to all biological and medical problems is known as biostatistics. Biostatisticians assist in the development of new approaches in various areas, including health and the environment. Biostatisticians are crucial because the quality of research work determine by the preparation of research activities, data collection, and reporting of results. Here, the ideals of biostatics come into play. The course designs to give you in-depth knowledge of the principles and methods of Biostatistics and help you understand the subject with ease.
Provider: BioTecNika Store
Subject: Biostatistics
Duration: Self Placed
Start Date: Open
Presents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, emphasizing one- and two-sample probability and analysis. Inference, including hypothesis checking and trust for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations are among the topics covered.
Students would need to update their mathematical, numerical, statistical, and probability backgrounds in order to take this course. Students will learn how to display and communicate statistical data in this course. It will provide graphical and exploratory data analysis with scatterplots, boxplots, and multivariate data visualization. Students will ask to write thoroughly for this objective.
Instructor: Brian Caffo
Provider: Johns Hopkins University
Subject: Biostatistics
Duration: Self Placed
Start Date: Open
Case studies will use to discuss problems and applications of biostatistics in this course. Cohort and case-control research, survival analysis of clinical trial applications, diagnostic test assessment, and statistical genetics will all be covered. A survey of current biostatistical research will present at the end of the course. This course is cross-listed with Statistics 449 in the Literature, Science and the Arts department.
Provider: University of Michigan
Subject: Biostatistics
Duration: NA
Start Date: Open
The second course in biostatistical methods and data processing using applied biostatistical methods. Data analysis and experimental design concepts for health-related research. Categorical data analysis, multiple regression, analysis of variance, and covariance are all highlighted.
Provider: University of Michigan
Instructor(s): Wu, Zhenke
Subject: Biostatistics
Duration: NA
Start Date: Open
It gives you a broad understanding of how biostatistics is used in regulatory settings and examines applicable rules and regulations and any related guidance papers. Basic research design, target population, reference groups, and endpoints are among the topics covered. Addresses problems with research, focusing on regulatory factors, such as missing data and insightful censoring. This article discusses safety management, interim review, and early trial termination with an emphasis on regulatory consequences.
Provider: Johns Hopkins University
Instructor(s): Mary Foulkes and Simon Day
Subject: Biostatistics
Duration: NA
Start Date: Open
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