Coursera Course: Mathematical Biostatistics Boot Camp 1

Coursera Course: Mathematical Biostatistics Boot Camp 1

University: Johns Hopkins University

Mathematical Biostatistics Classroom Session by Tutorteddy.com

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Coursera Course Description:

The course introduces us to the fundamentals of probability and statistical concepts that are used in the elementary data analysis. This particular course is an introductory level and is intended for the students having junior or senior college-level mathematical training that includes a practical knowledge of the calculus. A little knowledge about linear algebra and programming beforehand is an added advantage for the students, but it is not a necessity.

The knowledge of Statistics has become quite important nowadays as it provides the fundamental language of all experimental research. Biostatistics is a special field of statistics that can be applied to the biomedical sciences and research.

Both mathematical and statistical topics are included in this course to aid the students to understand biostatistics in details. After completion of the course, students will get a clear idea and good understanding about the assumptions, goals, advantages and disadvantages of probability modeling in the medical sciences. All these will help the students to approach new statistical topics and will help a lot to build a strong concept for future self learning and applications.

The following topics are included:

• The fundamentals and basics of probability theory.


• What are random variables?


• Discrete and Continuous distributions.


• Finding expectations and variances.


• Idea of independence and independent events


• Likelihood and basic inferences on confidence intervals.

Course Syllabus

The course emphasizes on applying core statistical concepts and methods to biostatistics and quantitative scientists.

• Basics of biostatistics and fundamentals of probability distributions and the properties of them are included which helps the students to build their basic knowledge.


• Inclusion of the idea of statistical likelihood.


• The concepts of confidence intervals are also provided.


• Students will know about the display and communication of statistical data that includes graphical representation of data and exploratory data analysis that makes use of the tools like box plots and scatter plots to display multivariate data.

Recommended Background

A prerequisite for the class is to have moderate level mathematical literacy, knowledge of set theory and calculus. An idea about programming is also useful though it is not required.

Course Format

Lectures and homework assignments forms the basis of the course.

FAQ

Is knowledge of Calculus a necessity for the course?

Yes