This course is part of the Advanced Statistics for Data Science Specialization

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stars
445 ratings

Brian Caffo, PhD

68,336 already enrolled

Offered By

Advanced Statistics for Data Science SpecializationJohns Hopkins University

About this Course

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This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.

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Shareable Certificate

Earn a Certificate upon completion

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Course 1 of 4 in the

Advanced Statistics for Data Science Specialization

Approx. 13 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish

Skills you will gain

Statistics
Confidence Interval
Statistical Hypothesis Testing
Biostatistics

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 4 in the

Advanced Statistics for Data Science Specialization

Approx. 13 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish

Instructor

Instructor rating

4.38/5 (68 Ratings)

Brian Caffo, PhD

Professor, Biostatistics

Bloomberg School of Public Health

1,488,172 Learners

30 Courses

Offered by

Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

Syllabus - What you will learn from this course

Content Rating94%(2,673 ratings)

Week

Week 1

4 hours to complete

Introduction, Probability, Expectations, and Random Vectors

You are about to undergo an intense and demanding immersion into the world of mathematical biostatistics. Over the next few weeks, you will learn about probability, expectations, conditional probabilities, distributions, confidence intervals, bootstrapping, binomial proportions, and much more. Module 1 covers experiments, probability, variables, mass functions, density functions, cumulative distribution functions, expectations, variations, and vectors.

4 hours to complete

13 videos (Total 179 min), 2 readings, 2 quizzes

13 videos

Welcome to the Course1m

Biostatistics and Experiments12m

Set Notation and Probability14m

Probability22m

Random Variables6m

PMFs and PDFs17m

CDFs, Survival Functions, and Quantiles11m

Expected Values12m

Rules About Expected Values10m

Variances and Chebyshev's Inequality18m

Random Vectors and Independence17m

Correlation10m

Variance Properties and Sample Variance22m

2 readings

Syllabus10m

Faculty10m

2 practice exercises

Module 1 Homework30m

Module 1 Quiz: Introduction, Probability, Expectations, and Random Vectors30m

Week

Week 2

4 hours to complete

Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics

This module covers Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics. These are the most fundamental core concepts in mathematical biostatistics and statistics. After this module you should be able to recognize and be functional in these key concepts.

4 hours to complete

7 videos (Total 157 min)

Week

Week 3

3 hours to complete

Confidence Intervals, Bootstrapping, and Plotting

This module covers Confidence Intervals, Bootstrapping, and Plotting. These are core concepts in mathematical biostatistics and statistics. After this module you should be able to recognize and be functional in these key concepts.

3 hours to complete

7 videos (Total 121 min)

Week

Week 4

2 hours to complete

Binomial Proportions and Logs

This module covers Binomial Proportions and Logs. These are core concepts in mathematical biostatistics and statistics. After this module you should be able to recognize and be functional in these key concepts.

2 hours to complete

3 videos (Total 71 min)

Reviews

4.4

103 reviews

5 stars
63.61%
4 stars
23.88%
3 stars
7.81%
2 stars
2.45%
1 star
2.23%

TOP REVIEWS FROM MATHEMATICAL BIOSTATISTICS BOOT CAMP 1

by BEApr 5, 2018

This course is phenomenally well developed with great curriculum and materials for building astrong base to enter into statistics with a strong base of knowledge.

by MCAug 30, 2017

The content is in-depth and the instructor is knowledgeable, but the quiz demands a quite wide knowledge base and does not provide feedback.

by FTJan 20, 2022

I like really course content but it would be better to add exlaination for quiz (especially when initial answer is wrong, now student can only see explainations when answer question right)

by MSMar 27, 2018

I liked the course. Need good maths skills. Would prefer to have a review/HW after each lecture than at the end of each week.

View all reviews

About the Advanced Statistics for Data Science Specialization

Fundamental concepts in probability, statistics and linear models are primary building blocks for data science work. Learners aspiring to become biostatisticians and data scientists will benefit from the foundational knowledge being offered in this specialization. It will enable the learner to understand the behind-the-scenes mechanism of key modeling tools in data science, like least squares and linear regression.

This specialization starts with Mathematical Statistics bootcamps, specifically concepts and methods used in biostatistics applications. These range from probability, distribution, and likelihood concepts to hypothesis testing and case-control sampling. This specialization also linear models for data science, starting from understanding least squares from a linear algebraic and mathematical perspective, to statistical linear models, including multivariate regression using the R programming language. These courses will give learners a firm foundation in the linear algebraic treatment of regression modeling, which will greatly augment applied data scientists' general understanding of regression models. This specialization requires a fair amount of mathematical sophistication. Basic calculus and linear algebra are required to engage in the content.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

Mathematical Biostatistics Boot Camp 1

About this Course

Skills you will gain