Univariate data analysis

Learning outcomes

• The study of variability important to help answer: "what happened?"
• Univariate tools such as the histogram, median, MAD, standard deviation, quartiles will be reviewed from prior courses (as a refresher)
• The normal and t-distribution will be important in our work: what are they, how to interpret them, and use tables of these distributions
• The central limit theorem will be explained conceptually: you cannot finish a course on stats without knowing the key result from this theorem.
• Using and interpreting confidence intervals will be crucial in all the modules that follow.

Extended readings

• New Boeing planes will generate 0.5 TB of data per flight. Read about this, and other sources of data: "every piece of that plane has an internet connection, from the engines to the flaps to the landing gear".
• All students, but especially the 600-level students should read the article by Peter J. Rousseeuw, Tutorial to Robust Statistics it is easy to read, and contains so much useful content.

Resources

• Class notes 2015
• Class notes 2014
• Textbook, chapter 2
• Complete steps 10, 11, 12 and 13 of the software tutorial
• A demonstration of R
• Using tables of the normal distribution

Class videos from prior years

Videos from 2015

Covered in class | No video | Script

Audio only | No video | Script

Audio only | No video | Script

Videos from 2014

See the webpage from 2014

Videos from 2013

See the webpage from 2013