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.
Este curso faz parte do Programa de cursos integrados Advanced Statistics for Data Science
oferecido por
Programa de cursos integrados Advanced Statistics for Data ScienceUniversidade Johns HopkinsInformações sobre o curso
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Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Aprox. 13 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Italiano, Vietnamita, Coreano, Alemão, Russo, Turco, Inglês, Espanhol
Habilidades que você terá
StatisticsConfidence IntervalStatistical Hypothesis TestingBiostatistics
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Aprox. 13 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Italiano, Vietnamita, Coreano, Alemão, Russo, Turco, Inglês, Espanhol
oferecido por
Universidade Johns Hopkins
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.
Programa - O que você aprenderá com este curso
4 horas para concluir
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.
4 horas para concluir
13 vídeos (Total 179 mín.), 2 leituras, 2 testes
13 videos
Biostatistics and Experiments12min
Set Notation and Probability14min
Probability22min
Random Variables6min
PMFs and PDFs17min
CDFs, Survival Functions, and Quantiles11min
Expected Values12min
Rules About Expected Values10min
Variances and Chebyshev's Inequality18min
Random Vectors and Independence17min
Correlation10min
Variance Properties and Sample Variance22min
2 leituras
Syllabus10min
Faculty10min
2 exercícios práticos
Module 1 Homework30min
Module 1 Quiz: Introduction, Probability, Expectations, and Random Vectors30min
4 horas para concluir
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.
4 horas para concluir
7 vídeos (Total 157 mín.)
7 videos
Bayes' Rule and DLRs23min
Likelihood32min
Bernoulli Distribution and Binomial Trials15min
The Normal Distribution28min
Limits and LLN18min
CLT and Confidence Intervals23min
2 exercícios práticos
Module 2 Homework30min
Module 2 Quiz: Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics30min
3 horas para concluir
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.
3 horas para concluir
7 vídeos (Total 121 mín.)
7 videos
Student's t Distribution and CI for Normal Means19min
Profile Likelihoods8min
T Confidence Intervals24min
Plotting22min
The Jackknife12min
Bootstrapping17min
2 exercícios práticos
Module 3 Homework30min
Module 3 Quiz: Confidence Intervals, Bootstrapping, and Plotting30min
2 horas para concluir
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.
2 horas para concluir
3 vídeos (Total 71 mín.)
2 exercícios práticos
Module 4 Homework30min
Module 4 Quiz: Binomial Proportions and Logs30min
Avaliações
Principais avaliações do BIOESTATÍSTICA MATEMÁTICA: TREINAMENTO 1
por DH4 de Jun de 2017
I knew a lot about probability before starting this course, but I didn't know much of anything about frequentist statistics. This course helped me understand some tricky concepts.
por PB11 de Jan de 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.
por JB8 de Jul de 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.
por BE5 de Abr de 2018
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.
Sobre Programa de cursos integrados Advanced Statistics for Data Science
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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