Mathematical Biostatistics Boot Camp 1

Mathematical Biostatistics Boot Camp 1

This course is part of Advanced Statistics for Data Science Specialization

Instructor: Brian Caffo, PhD

Access provided by KAUST Academy learning programs

88,268 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

538 reviews

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

95%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

538 reviews

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

95%

Most learners liked this course

Skills you'll gain

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Assessments

8 assignments

Taught in English

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

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There are 4 modules in 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.

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.

What's included

13 videos2 readings2 assignments

13 videos Total 179 minutes

Welcome to the Course 1 minute
Biostatistics and Experiments 13 minutes
Set Notation and Probability 15 minutes
Probability 23 minutes
Random Variables 6 minutes
PMFs and PDFs 18 minutes
CDFs, Survival Functions, and Quantiles 12 minutes
Expected Values 13 minutes
Rules About Expected Values 10 minutes
Variances and Chebyshev's Inequality 19 minutes
Random Vectors and Independence 18 minutes
Correlation 11 minutes
Variance Properties and Sample Variance 22 minutes

2 readings Total 20 minutes

Syllabus 10 minutes
Faculty 10 minutes

2 assignments Total 60 minutes

Module 1 Quiz: Introduction, Probability, Expectations, and Random Vectors 30 minutes
Module 1 Homework 30 minutes

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.

What's included

7 videos2 assignments

7 videos Total 157 minutes

Conditional Probabilities and Densities 14 minutes
Bayes' Rule and DLRs 24 minutes
Likelihood 32 minutes
Bernoulli Distribution and Binomial Trials 16 minutes
The Normal Distribution 28 minutes
Limits and LLN 19 minutes
CLT and Confidence Intervals 24 minutes

2 assignments Total 60 minutes

Module 2 Quiz: Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics 30 minutes
Module 2 Homework 30 minutes

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.

What's included

7 videos2 assignments

7 videos Total 121 minutes

Confidence Intervals and CI for Normal Variance 16 minutes
Student's t Distribution and CI for Normal Means 19 minutes
Profile Likelihoods 8 minutes
T Confidence Intervals 25 minutes
Plotting 23 minutes
The Jackknife 13 minutes
Bootstrapping 17 minutes

2 assignments Total 60 minutes

Module 3 Quiz: Confidence Intervals, Bootstrapping, and Plotting 30 minutes
Module 3 Homework 30 minutes

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.

What's included

3 videos2 assignments

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Instructor

Instructor ratings

(93 ratings)

Brian Caffo, PhD

Johns Hopkins University

30 Courses 1,707,467 learners

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Johns Hopkins University

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Reviewed on Jan 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.

Reviewed on Jan 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)

Reviewed on Jul 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.

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