- Level Foundation
- Duration 13 hours
- Course by Johns Hopkins University
-
Offered by
About
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.Modules
Welcome
1
Videos
- Welcome to the Course
2
Readings
- Syllabus
- Faculty
Experiments and Probability
2
Videos
- Biostatistics and Experiments
- Set Notation and Probability
Probability and Variables
2
Videos
- Probability
- Random Variables
Probability Mass Functions, Probability Density Functions, and Cumulative Distribution Functions
2
Videos
- PMFs and PDFs
- CDFs, Survival Functions, and Quantiles
Expected Values, Variances, and Standard Deviation
3
Videos
- Expected Values
- Rules About Expected Values
- Variances and Chebyshev's Inequality
Random Vectors, Independent Events and Variables, Covariance and Correlation, and Sample Variance
3
Videos
- Random Vectors and Independence
- Correlation
- Variance Properties and Sample Variance
Review
2
Assignment
- Module 1 Homework
- Module 1 Quiz: Introduction, Probability, Expectations, and Random Vectors
Conditional Probabilities and and Bayes' Rule
2
Videos
- Conditional Probabilities and Densities
- Bayes' Rule and DLRs
Likelihood Plots and Ratio Benchmarks
1
Videos
- Likelihood
Bernoulli, Binomial, and Normal Distributions
2
Videos
- Bernoulli Distribution and Binomial Trials
- The Normal Distribution
Limits, the Law of Large Numbers, the Central Limit Theorem, and Confidence Intervals
2
Videos
- Limits and LLN
- CLT and Confidence Intervals
Review
2
Assignment
- Module 2 Homework
- Module 2 Quiz: Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics
Chi-squared and t-Distributions, Confidence Intervals, and Likelihoods
3
Videos
- Confidence Intervals and CI for Normal Variance
- Student's t Distribution and CI for Normal Means
- Profile Likelihoods
Confidence Intervals
1
Videos
- T Confidence Intervals
All About Plotting
1
Videos
- Plotting
Bootstrap Principle, Algorithm, and Calculations
2
Videos
- The Jackknife
- Bootstrapping
Review
2
Assignment
- Module 3 Homework
- Module 3 Quiz: Confidence Intervals, Bootstrapping, and Plotting
Binomial Proportions, the Wald Interval, and Bayesian Analysis
2
Videos
- Binomial Proportions Part A
- Binomial Proportions Part B
Logs and the Geometric Mean
1
Videos
- Logs
Review
2
Assignment
- Module 4 Homework
- Module 4 Quiz: Binomial Proportions and Logs
Auto Summary
Unlock the essential principles of data analysis with the "Mathematical Biostatistics Boot Camp 1" course. This foundational program delves into critical probability and statistical concepts tailored for those with a background in junior or senior college-level mathematics. While a basic understanding of calculus is essential, familiarity with linear algebra and programming can enhance your learning experience but are not mandatory prerequisites. Crafted by experts at Coursera, this course spans approximately 780 minutes of comprehensive content designed to build your proficiency in biostatistics. Ideal for beginners and those looking to solidify their foundational knowledge, the program offers a structured yet flexible learning path under the "Starter" subscription plan. Join a community of learners eager to grasp the quantitative methods necessary for elementary data analysis and elevate your skills in the domain of maths and statistics. Whether you're pursuing academic excellence or seeking to apply these concepts professionally, this course is your gateway to mastering the fundamentals of biostatistics.

Brian Caffo, PhD