Difference between revisions of "Univariate data analysis"

Revision as of 19:14, 2 January 2016

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.

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.

Tasks to do first	Quiz	Solution
Complete steps 10, 11, 12 and 13 of the software tutorial (also steps 1 through 9)	Quiz	Solution
Watch videos 1, 2, 3 and 4	Quiz	Solution
Watch videos 7, 8 and 9	Quiz	Solution
Watch videos 10, 11, and 12	Quiz	Solution
Watch videos 13, 14	Quiz	Solution
Watch videos 15, 16	Quiz	Solution

Introduction [05:59]
Histograms [04:50]
Basic terminology [06:41]
Outliers, medians and MAD [04:42]
The central limit theorem [06:56]
The normal distribution, and standardizing variables [05:54]
Normal distribution notation and using tables and R [05:48]
Checking if data are normally distributed [05:57]
Introducing the idea of a confidence interval [covered in class]
Confidence intervals when we don't know the variance [07:59]
Interpreting the confidence interval [07:52]
A worked example: calculating and interpreting the CI [03:37]
A motivating example to see why tests for differences are important [08:29]
The mathematical derivation for a confidence interval for differences [covered in class]
Using the confidence interval to test for differences to solve the motivating example [covered in class]
Confidence intervals for paired tests: theory and an example [11:59]

Covered in class | No video | Script

Audio only | No video | Script

@@ Line 17: / Line 17: @@
 :{| class="wikitable"
 |-
-! Videos to watch first
+! Tasks to do first
 ! Quiz
 ! Solution
 |-
-| Watch videos 1, 2 and 3
+| Complete steps 10, 11, 12 and 13 of the [http://learnche.mcmaster.ca/4C3/Software_tutorial software tutorial]
+(also steps 1 through 9)
 | [https://docs.google.com/document/d/1UHoVz0Gi9eazCYpvtIzRlP79RmjtjxERS5xka5ZBkps Quiz]
 | [https://docs.google.com/document/d/1lMSDnUVTZ6X-uIbC7iUc1UKk7QvQWrngm8LDm1r8RuI Solution]
 |-
-| Watch videos 4, 5 and 6
+| Watch videos 1, 2, 3 and 4
 | [https://docs.google.com/document/d/19NnM1v7yut1q0HFaHMQmNg6zMH2UPN1rrHZl7l38qBI  Quiz]
 | [https://docs.google.com/document/d/1YcF4PxxfQqnz4UqgGZMWv3zfFmmjB7uSkNfQ9XMe97A Solution]
@@ Line 45: / Line 46: @@
 | [https://docs.google.com/document/d/10h2qavaw08AYC5qGAWyemXrgro0F-ARBaDnoE52S77Y Solution]
 |}
-* Complete steps 10, 11, 12 and 13 of the [http://learnche.mcmaster.ca/4C3/Software_tutorial software tutorial]
 * A [http://www.r-fiddle.org/#/fiddle?id=49eUbRMk demonstration of R]
 * [[Tables_of_the_normal_and_t-distribution| Using tables of the normal distribution]]