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

4.4
stars
462 ratings

Brian Caffo, PhD

71,498 already enrolled

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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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Course 1 of 4 in the

Advanced Statistics for Data Science Specialization

Approx. 13 hours to complete

English

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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

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.35/5 (72 Ratings)

Brian Caffo, PhD

Professor, Biostatistics

Bloomberg School of Public Health

1,522,748 Learners

30 Courses

Offered by

Johns Hopkins University

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Syllabus - What you will learn from this course

Content Rating94%(2,767 ratings)

Week1

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 Course1mBiostatistics and Experiments12mSet Notation and Probability14mProbability22mRandom Variables6mPMFs and PDFs17mCDFs, Survival Functions, and Quantiles11mExpected Values12mRules About Expected Values10mVariances and Chebyshev's Inequality18mRandom Vectors and Independence17mCorrelation10mVariance Properties and Sample Variance22m

2 readings

Syllabus10mFaculty10m

2 practice exercises

Module 1 Homework30mModule 1 Quiz: Introduction, Probability, Expectations, and Random Vectors30m

Week2

Week 2

4 hours to complete

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

4 hours to complete

7 videos (Total 157 min)

Week3

Week 3

3 hours to complete

Confidence Intervals, Bootstrapping, and Plotting

3 hours to complete

7 videos (Total 121 min)

Week4

Week 4

2 hours to complete

Binomial Proportions and Logs

2 hours to complete

3 videos (Total 71 min)

Reviews

4.4

107 reviews

5 stars
63.49%
4 stars
23.97%
3 stars
7.99%
2 stars
2.37%
1 star
2.15%

TOP REVIEWS FROM MATHEMATICAL BIOSTATISTICS BOOT CAMP 1

by DHJun 4, 2017

I knew a lot about probability before starting this course, but I didn't know much of anything about frequentist statistics. This course helped me understand some tricky concepts.

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.

by PBJan 11, 2016

Very concise, well-presented course. This was my second time taking it as a refresher. Prof. Caffo does a great job presenting the materials. However, prepare to be challenged.

by MLNov 26, 2015

I wish this Johns Hopkins course is more interactive. Like the Ohio State Calculus One class.

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.

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Mathematical Biostatistics Boot Camp 1

About this Course

Skills you will gain