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.
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귀하가 습득할 기술
- Statistics
- Confidence Interval
- Statistical Hypothesis Testing
- Biostatistics
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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.
강의 계획표 - 이 강좌에서 배울 내용
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.
검토
- 5 stars63.47%
- 4 stars24.42%
- 3 stars7.76%
- 2 stars2.05%
- 1 star2.28%
MATHEMATICAL BIOSTATISTICS BOOT CAMP 1의 최상위 리뷰
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.
I wish this Johns Hopkins course is more interactive. Like the Ohio State Calculus One class.
Not your average Coursera Course! Actually challenging. Brian Caffo's voice sounds a bit likw Sheldon Cooper!
Topics presented well for comprehension, good lecture quality. These topics are covered in grad level statistics courses at certain universities.
Advanced Statistics for Data Science 특화 과정 정보
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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