Key Information
About the content
This course is an introduction to the key ideas and principles of the collection, display, and analysis of data to guide you in making valid and appropriate conclusions about the world.
Syllabus
A first look at data
Weeks 1-2: Summary statistics and graphical displays for a single categorical or quantitative variable and for relationships between two variables.
Collecting data
Week 2: Sampling. Observational studies and experiments. The effect of confounding and concluding causation.
Probability
Week 3: Probability models, the normal distribution, the Law of Large Numbers, the Central Limit Theorem, sampling distributions.
Confidence Intervals
Week 4: Confidence intervals and sample size estimation for proportions and means.
Tests of significance
Week 5: Tests of significance, power and sample size estimation for proportions and means
Two samples
Week 6: Tests of significance and confidence intervals for proportions and means in the two sample case.
Simple linear regression
Week 7: Method of least squares, evaluating model fit, the effects of outliers and influential observations.
The process of statistical inquiry
Week 8: Capstone case study.
Instructors
- Alison Gibbs - Department of Statistical Sciences
- Jeffrey Rosenthal - Department of Statistical Sciences
Content Designer
Platform
Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California.
Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.
