Informações sobre o curso: Este curso apresenta a probabilidade fundamental e conceitos estatísticos usados na análise de dados elementares. Ele vai ser ensinado a um nível introdutório para estudantes com formação matemática de nível universitário júnior ou sênior, incluindo um conhecimento prático de cálculo. Uma pequena quantidade de álgebra linear e programação são úteis para o curso, mas não é obrigatório.
Desenvolvido por: Universidade Johns Hopkins
Ministrado por: Brian Caffo, PhD, Professor, Biostatistics
Bloomberg School of Public Health
| Compromisso | 3-5 horas/semana |
| Idioma | English |
| Como ser aprovado | Seja aprovado em todas as tarefas para concluir o curso. |
| Classificação do usuário |
Programa
SEMANA 1
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.
13 vídeos, 2 leituras, 1 questionário de prática
- Vídeo: Welcome to the Course
- Reading: Syllabus
- Reading: Faculty
- Vídeo: Biostatistics and Experiments
- Vídeo: Set Notation and Probability
- Vídeo: Probability
- Vídeo: Random Variables
- Vídeo: PMFs and PDFs
- Vídeo: CDFs, Survival Functions, and Quantiles
- Vídeo: Expected Values
- Vídeo: Rules About Expected Values
- Vídeo: Variances and Chebyshev's Inequality
- Vídeo: Random Vectors and Independence
- Vídeo: Correlation
- Vídeo: Variance Properties and Sample Variance
- Practice Quiz: Module 1 Homework
Nota atribuída: Module 1 Quiz: Introduction, Probability, Expectations, and Random Vectors
SEMANA 2
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.
7 vídeos, 1 questionário de prática
- Vídeo: Conditional Probabilities and Densities
- Vídeo: Bayes' Rule and DLRs
- Vídeo: Likelihood
- Vídeo: Bernoulli Distribution and Binomial Trials
- Vídeo: The Normal Distribution
- Vídeo: Limits and LLN
- Vídeo: CLT and Confidence Intervals
- Practice Quiz: Module 2 Homework
Nota atribuída: Module 2 Quiz: Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics
SEMANA 3
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.
7 vídeos, 1 questionário de prática
- Vídeo: Confidence Intervals and CI for Normal Variance
- Vídeo: Student's t Distribution and CI for Normal Means
- Vídeo: Profile Likelihoods
- Vídeo: T Confidence Intervals
- Vídeo: Plotting
- Vídeo: The Jackknife
- Vídeo: Bootstrapping
- Practice Quiz: Module 3 Homework
Nota atribuída: Module 3 Quiz: Confidence Intervals, Bootstrapping, and Plotting
SEMANA 4
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.
3 vídeos, 1 questionário de prática
- Vídeo: Binomial Proportions Part A
- Vídeo: Binomial Proportions Part B
- Vídeo: Logs
- Practice Quiz: Module 4 Homework
Nota atribuída: Module 4 Quiz: Binomial Proportions and Logs
Perguntas frequentes
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Coursework
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Desenvolvedores
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.
Classificações e avaliações
Hopefully It can be more related to Bios, Yet it's a amazing course for stat.
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 liked the course. Need good maths skills. Would prefer to have a review/HW after each lecture than at the end of each week.
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SY
Nice class!