About this course: 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.
Created by: Johns Hopkins University
Taught by: Brian Caffo, PhD, Professor, Biostatistics
Bloomberg School of Public Health
| Commitment | 3-5 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
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.
13 videos, 2 readings, 1 practice quiz
- Reading: Syllabus
- Reading: Faculty
- Video: Biostatistics and Experiments
- Video: Set Notation and Probability
- Video: Probability
- Video: Random Variables
- Video: PMFs and PDFs
- Video: CDFs, Survival Functions, and Quantiles
- Video: Expected Values
- Video: Rules About Expected Values
- Video: Variances and Chebyshev's Inequality
- Video: Random Vectors and Independence
- Video: Correlation
- Video: Variance Properties and Sample Variance
- Тренировочный тест: Module 1 Homework
Graded: Module 1 Quiz: Introduction, Probability, Expectations, and Random Vectors
WEEK 2
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.
7 videos, 1 practice quiz
- Video: Bayes' Rule and DLRs
- Video: Likelihood
- Video: Bernoulli Distribution and Binomial Trials
- Video: The Normal Distribution
- Video: Limits and LLN
- Video: CLT and Confidence Intervals
- Тренировочный тест: Module 2 Homework
Graded: Module 2 Quiz: Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics
WEEK 3
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.
7 videos, 1 practice quiz
- Video: Student's t Distribution and CI for Normal Means
- Video: Profile Likelihoods
- Video: T Confidence Intervals
- Video: Plotting
- Video: The Jackknife
- Video: Bootstrapping
- Тренировочный тест: Module 3 Homework
Graded: Module 3 Quiz: Confidence Intervals, Bootstrapping, and Plotting
WEEK 4
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.
3 videos, 1 practice quiz
- Video: Binomial Proportions Part B
- Video: Logs
- Тренировочный тест: Module 4 Homework
Graded: Module 4 Quiz: Binomial Proportions and Logs
FAQs
How It Works
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Creators
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.
Ratings and Reviews
Love the course, and its willingness to delve into the basics of the theory behind biostatistics. Wish there were more like it.
Content is very good but please make it more MOOC friendly. More diagrams and animations to help visualize concepts would be useful. Also try to give more layman explanations for concepts getting through stats jargon was sometimes a struggle. Overall a pleasing course though!
This is a very worthful course to SUFFER! I'd like to say, no camp, no gain. In addition to the statistics with math, I experience how important of "hang on there and never give up"!I'm going to the camp 2 to see what's gonna happen.
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V
Great course, excellent homework/quizzes and comparatively rigorous treatment by a great Prof.