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.
This course is part of the Advanced Statistics for Data Science Specialization
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Advanced Statistics for Data Science SpecializationJohns Hopkins UniversityAbout this Course
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Course 1 of 4 in the
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Approx. 13 hours to complete
English
Subtitles: French, Portuguese (Brazilian), Russian, English, Spanish
Skills you will gain
StatisticsConfidence IntervalStatistical Hypothesis TestingBiostatistics
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 1 of 4 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 13 hours to complete
English
Subtitles: French, Portuguese (Brazilian), Russian, English, Spanish
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
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
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
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)
7 videos
Bayes' Rule and DLRs23m
Likelihood32m
Bernoulli Distribution and Binomial Trials15m
The Normal Distribution28m
Limits and LLN18m
CLT and Confidence Intervals23m
2 practice exercises
Module 2 Homework30m
Module 2 Quiz: Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics30m
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)
7 videos
Student's t Distribution and CI for Normal Means19m
Profile Likelihoods8m
T Confidence Intervals24m
Plotting22m
The Jackknife12m
Bootstrapping17m
2 practice exercises
Module 3 Homework30m
Module 3 Quiz: Confidence Intervals, Bootstrapping, and Plotting30m
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)
2 practice exercises
Module 4 Homework30m
Module 4 Quiz: Binomial Proportions and Logs30m
Reviews
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 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 JBJul 8, 2017
Great course, though a little difficult in parts, particularly the first week. Worth working through though for a better understanding of probability and statistics.
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.
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.
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, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
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