数据科学与分析的统计思维

Statistical Thinking for Data Science and Analytics

Learn how statistics plays a central role in the data science approach.

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哥伦比亚大学
edX
  • 完成时间大约为 5
  • 初级
  • 英语
注:因开课平台的各种因素变化,以上开课日期仅供参考

你将学到什么

Data collection, analysis and inference

Data classification to identify key traits and customers

Conditional Probability-How to judge the probability of an event, based on certain conditions

How to use Bayesian modeling and inference for forecasting and studying public opinion

Basics of Linear Regression

Data Visualization: How to create use data to create compelling graphics

课程概况

This statistics and data analysis course will pave the statistical foundation for our discussion on data science.

You will learn how data scientists exercise statistical thinking in designing data collection, derive insights from visualizing data, obtain supporting evidence for data-based decisions and construct models for predicting future trends from data.

课程大纲

Week 1 – Introduction to Data Science

Week 2 – Statistical Thinking

Examples of Statistical Thinking
Numerical Data, Summary Statistics
From Population to Sampled Data
Different Types of Biases
Introduction to Probability
Introduction to Statistical Inference

Week 3 – Statistical Thinking 2

Association and Dependence
Association and Causation
Conditional Probability and Bayes Rule
Simpsons Paradox, Confounding
Introduction to Linear Regression
Special Regression Models

Week 4 – Exploratory Data Analysis and Visualization

Goals of statistical graphics and data visualization
Graphs of Data
Graphs of Fitted Models
Graphs to Check Fitted Models
What makes a good graph?
Principles of graphics

Week 5 – Introduction to Bayesian Modeling

Bayesian inference: combining models and data in a forecasting problem
Bayesian hierarchical modeling for studying public opinion
Bayesian modeling for Big Data

预备知识

High School Math. Some exposure to computer programming.

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