Developing insights about your organization, business, or research project depends on effective modeling and analysis of the data you collect. Building effective models requires understanding the different types of questions you can ask and how to map those questions to your data. Different modeling approaches can be chosen to detect interesting patterns in the data and identify hidden relationships.
课程信息
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第 5 门课程（共 5 门）
完成时间大约为21 小时
英语（English）
字幕：英语（English）
您将学到的内容有
Describe different types of data analytic questions
Conduct hypothesis tests of your data
Apply linear modeling techniques to answer multivariable questions
Apply machine learning workflows to detect complex patterns in your data
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 5 门课程（共 5 门）
完成时间大约为21 小时
英语（English）
字幕：英语（English）
提供方
约翰霍普金斯大学
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.
授课大纲 - 您将从这门课程中学到什么
完成时间为 4 小时
Modeling Data Basics
Developing insights about your organization, business, or research project depends on effective modeling and analysis of the data you collect. Building effective models requires understanding the different types of questions you can ask and how to map those questions to your data. Different modeling approaches can be chosen to detect interesting patterns in the data and identify hidden relationships.
完成时间为 4 小时
16 个阅读材料
完成时间为 1 小时
Inference
Inferential Analysis is what analysts carry out after they’ve described and explored their dataset. After understanding your dataset better, analysts often try to infer something from the data. This is done using statistical tests. We discussed a bit about how we can use models to perform inference and prediction analyses. What does this mean?
完成时间为 1 小时
3 个阅读材料
完成时间为 2 小时
Linear Modeling
Linear models are the most commonly used models in data analysis because of their computational efficiency and their ease of interpretation. Having a solid understanding of linear models and how they work is critical for any work in data science. The tidyverse provides a set of tools for making linear modeling more efficient and streamlined.
完成时间为 2 小时
12 个阅读材料
完成时间为 1 小时
Multiple Linear Regression
Multiple linear regression is needed when you want to include confounding factors or other predictors in your model for the response. R provides a straightforward way to do this via the formula interface to the lm() function.
完成时间为 1 小时
1 个阅读材料
关于 Tidyverse Skills for Data Science in R 专项课程
This Specialization is intended for data scientists with some familiarity with the R programming language who are seeking to do data science using the Tidyverse family of packages. Through 5 courses, you will cover importing, wrangling, visualizing, and modeling data using the powerful Tidyverse framework. The Tidyverse packages provide a simple but powerful approach to data science which scales from the most basic analyses to massive data deployments. This course covers the entire life cycle of a data science project and presents specific tidy tools for each stage.
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