## Data Analysis and Statistical Inference

 所在平台: Coursera 课程类别: 统计和数据分析 大学或机构: Duke University(杜克大学)

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#### 课程详情

The goals of this course are as follows:

1. Recognize the importance of data collection, identify limitations in data collection methods, and determine how they affect the scope of inference.
2. Use statistical software (R) to summarize data numerically and visually, and to perform data analysis.
3. Have a conceptual understanding of the unified nature of statistical inference.
4. Apply estimation and testing methods (confidence intervals and hypothesis tests) to analyze single variables and the relationship between two variables in order to understand natural phenomena and make data-based decisions.
5. Model and investigate relationships between two or more variables within a regression framework.
6. Interpret results correctly, effectively, and in context without relying on statistical jargon.
7. Critique data-based claims and evaluate data-based decisions.
8. Complete a research project that employs simple statistical inference and modeling techniques.

#### 课程大纲

• Week 1: Unit 1 - Introduction to data
• Week 2: Unit 2 - Probability and distributions
• Weeks 3 & 4: Unit 3 - Foundations for inference + Midterm
• Week 5: Unit 4 - Statistical inference for numerical variables
• Week 6: Unit 5 - Statistical inference for categorical variables
• Week 7: Unit 6 - Simple linear regression
• Week 8: Unit 7 - Multiple linear regression
• Week 9: Capstone project
• Week 10: Final exam

#### 课程评论(1条)

 0 Nano环境微生物 2014-11-20 11:47 0 票支持; 0 票反对 刚上完第二门在MOOC上的课。总的说，不错很赞。本科如果在国内好好上过数理统计的话，上这门课会感觉互补性很强。老师比较注意概念和实际的例子，把贝叶斯和simulation的概念讲得非常清楚。R语言也是第一次学，比较简单，容易上手。当然不足的地方，就是数学推导全部跳过了；不过随便找一本国内工科数理统计的教材对照学，效果就更好了。

#### 课程简介

This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.