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.
提供方
课程信息
您将获得的技能
- Statistics
- Confidence Interval
- Statistical Hypothesis Testing
- Biostatistics
提供方

约翰霍普金斯大学
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.
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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.
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.
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.
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.
审阅
- 5 stars63.47%
- 4 stars24.42%
- 3 stars7.76%
- 2 stars2.05%
- 1 star2.28%
来自数学生物统计学入门 1的热门评论
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)
Brian Caffo is the best statistics teacher I have ever had. I like how he breaks down things and he covers the ways to think about statistics far beyond any course I have taken.
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.
I think this a good course for practicing concepts, but the quizzes are not quite appropriate for a beginner's course.
关于 Advanced Statistics for Data Science 专项课程
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.

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