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StatisticsConfidence IntervalStatistical Hypothesis TestingBiostatistics

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### 提供方 1

## Introduction, Probability, Expectations, and Random Vectors

13 個視頻 （總計 179 分鐘）, 2 個閱讀材料, 2 個測驗
13 個視頻
Biostatistics and Experiments12分鐘
Set Notation and Probability14分鐘
Probability22分鐘
Random Variables6分鐘
PMFs and PDFs17分鐘
CDFs, Survival Functions, and Quantiles11分鐘
Expected Values12分鐘
Variances and Chebyshev's Inequality18分鐘
Random Vectors and Independence17分鐘
Correlation10分鐘
Variance Properties and Sample Variance22分鐘
2 個閱讀材料
Syllabus10分鐘
Faculty10分鐘
2 個練習
Module 1 Homework30分鐘
Module 1 Quiz: Introduction, Probability, Expectations, and Random Vectors30分鐘
2

## Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics

7 個視頻 （總計 157 分鐘）
7 個視頻
Bayes' Rule and DLRs23分鐘
Likelihood32分鐘
Bernoulli Distribution and Binomial Trials15分鐘
The Normal Distribution28分鐘
Limits and LLN18分鐘
CLT and Confidence Intervals23分鐘
2 個練習
Module 2 Homework30分鐘
Module 2 Quiz: Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics30分鐘
3

## Confidence Intervals, Bootstrapping, and Plotting

7 個視頻 （總計 121 分鐘）
7 個視頻
Student's t Distribution and CI for Normal Means19分鐘
Profile Likelihoods8分鐘
T Confidence Intervals24分鐘
Plotting22分鐘
The Jackknife12分鐘
Bootstrapping17分鐘
2 個練習
Module 3 Homework30分鐘
Module 3 Quiz: Confidence Intervals, Bootstrapping, and Plotting30分鐘
4

## Binomial Proportions and Logs

3 個視頻 （總計 71 分鐘）
3 個視頻
Binomial Proportions Part B36分鐘
Logs27分鐘
2 個練習
Module 4 Homework30分鐘
Module 4 Quiz: Binomial Proportions and Logs30分鐘

## 關於 Advanced Statistics for Data Science 專項課程

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. This specialization starts with Mathematical Statistics bootcamps, specifically concepts and methods used in biostatistics applications. These range from probability, distribution, and likelihood concepts to hypothesis testing and case-control sampling. This specialization also linear models for data science, starting from understanding least squares from a linear algebraic and mathematical perspective, to statistical linear models, including multivariate regression using the R programming language. These courses will give learners a firm foundation in the linear algebraic treatment of regression modeling, which will greatly augment applied data scientists' general understanding of regression models. This specialization requires a fair amount of mathematical sophistication. Basic calculus and linear algebra are required to engage in the content.... 