Data Analysis and Statistical Inference

开始时间: 待定 持续时间: Unknown

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)

授课老师: Mine Çetinkaya-Rundel



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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.


  • 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



Nano环境微生物 2014-11-20 11:47 0 票支持; 0 票反对


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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.


杜克大学 duke 数据分析 统计 统计学 统计推断 线性回归 R 数据挖掘