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.
Ce cours fait partie de la Spécialisation Advanced Statistics for Data Science
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Spécialisation Advanced Statistics for Data ScienceUniversité Johns-HopkinsÀ propos de ce cours
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Approx. 13 heures pour terminer
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Compétences que vous acquerrez
StatisticsConfidence IntervalStatistical Hypothesis TestingBiostatistics
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 1 sur 4 dans le
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Approx. 13 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (brésilien), Italien, Vietnamien, Coréen, Allemand, Russe, Turc, Anglais, Espagnol, Chinois
Offert par
Université 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.
Programme du cours : ce que vous apprendrez dans ce cours
4 heures pour terminer
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 heures pour terminer
13 vidéos (Total 179 min), 2 lectures, 2 quiz
13 vidéos
Biostatistics and Experiments12 min
Set Notation and Probability14 min
Probability22 min
Random Variables6 min
PMFs and PDFs17 min
CDFs, Survival Functions, and Quantiles11 min
Expected Values12 min
Rules About Expected Values10 min
Variances and Chebyshev's Inequality18 min
Random Vectors and Independence17 min
Correlation10 min
Variance Properties and Sample Variance22 min
2 lectures
Syllabus10 min
Faculty10 min
2 exercices pour s'entraîner
Module 1 Homework30 min
Module 1 Quiz: Introduction, Probability, Expectations, and Random Vectors30 min
4 heures pour terminer
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 heures pour terminer
7 vidéos (Total 157 min)
7 vidéos
Bayes' Rule and DLRs23 min
Likelihood32 min
Bernoulli Distribution and Binomial Trials15 min
The Normal Distribution28 min
Limits and LLN18 min
CLT and Confidence Intervals23 min
2 exercices pour s'entraîner
Module 2 Homework30 min
Module 2 Quiz: Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics30 min
3 heures pour terminer
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 heures pour terminer
7 vidéos (Total 121 min)
7 vidéos
Student's t Distribution and CI for Normal Means19 min
Profile Likelihoods8 min
T Confidence Intervals24 min
Plotting22 min
The Jackknife12 min
Bootstrapping17 min
2 exercices pour s'entraîner
Module 3 Homework30 min
Module 3 Quiz: Confidence Intervals, Bootstrapping, and Plotting30 min
2 heures pour terminer
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 heures pour terminer
3 vidéos (Total 71 min)
2 exercices pour s'entraîner
Module 4 Homework30 min
Module 4 Quiz: Binomial Proportions and Logs30 min
Avis
Meilleurs avis pour BIOSTATISTIQUE MATHÉMATIQUE COURS INTENSIF 1
par DH4 juin 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.
par PB11 janv. 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.
par JB8 juil. 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.
par BE5 avr. 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.
À propos du Spécialisation 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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