This course introduces learners to the analysis of binary/dichotomous outcomes. Learners will become familiar with fundamental tests for two-group comparisons and statistical inference plus prediction more broadly using logistic regression. They will understand the connection between prevalence, risk ratios, and odds ratios. By the end of this course, learners will be able to understand how binary outcomes arise, how to use R to compare proportions between two groups, how to fit logistic regressions in R, how to make predictions using logistic regression, and how to assess the quality of these predictions. All concepts taught in this course will be covered with multiple modalities: slide-based lectures, guided coding practice with the instructor, and independent but structured exercises.
Logistic Regression and Prediction for Health Data
本课程是 Data Science for Health Research 专项课程 的一部分
包含在 
中
您将学到什么
Understand how binary outcomes arise and know the difference between prevalence, risk ratios, and odds ratios
Use logistic regression to estimate and interpret the association between one or more predictors and a binary outcome
Understand the principles for using logistic regression to make predictions and assessing the quality of those predictions
您将获得的技能
要了解的详细信息
添加到您的领英档案
7 项作业
了解顶级公司的员工如何掌握热门技能
积累特定领域的专业知识
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- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有3个模块
This module introduces you to binary outcomes, including how they arise, how to calculate proportions, and how to compare proportions between two groups.
涵盖的内容
11个视频8篇阅读材料2个作业3个讨论话题
In this module, you will be introduced to the ubiquitous logistic regression, one of the most common tools for measuring the association between one or more predictors and a binary outcome.
涵盖的内容
11个视频2篇阅读材料3个作业
This module introduces you to tools for assessing the quality of a fitted logistic regression model.
涵盖的内容
16个视频3篇阅读材料2个作业1个讨论话题
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