Difference between revisions of "Lectures: Stat 202 Summer 2016"

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* Homework: We spent most of the day's class working on [[Media:Stat202_2015S_HW18.pdf|''Homework 18 (Sampling Distributions)'']].  Due August 3, 2016.
 
* Homework: We spent most of the day's class working on [[Media:Stat202_2015S_HW18.pdf|''Homework 18 (Sampling Distributions)'']].  Due August 3, 2016.
  
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* Handout: A brief lecture during this day's class concerned a handout the [[Media:Stat202_T_Stats.pdf|T Statistics]].
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* Handout: A brief lecture during this day's class concerned a handout about [[Media:Stat202_T_Stats.pdf|T Statistics]].
  
 
* Reading: Moore, McCabe & Craig, pages 301-316: Sampling Distributions.
 
* Reading: Moore, McCabe & Craig, pages 301-316: Sampling Distributions.
  
 
* Reading: Moore, McCabe & Craig, pages 417-441: T Statistics.
 
* Reading: Moore, McCabe & Craig, pages 417-441: T Statistics.

Revision as of 02:30, 28 July 2016

Some lectures below reference my class notes. Here is a link to a recent version of the entire class notes document: The Data Professor's Guide to Basic Statistics. Following the same link in the future may bring you to a more recent version. The link will be as recent as I bother to update it.

Monday, June 27, 2016

  • Review assignment: Please review the material presented in class. We covered three and a half chapters (items 6-83, pages 13-27) in The Data Professor's Guide to Basic Statistics. These chapter's were Defining familiar terms, Let's collect some data!, Concepts of structured data, and part of Kinds of variables (up to item 83).
  • Reading: Moore, McCabe & Craig, pages 1-3.
  • Homework: problems 1.14 and 1.16 on Homework 1. Due date will be assigned later (a week in advance). Update: due July 6, 2016.


Tuesday, June 28, 2016

  • Reading: Moore, McCabe & Craig, Section 1.2, pages 9-25.


Wednesday, June 29, 2016

  • Reading: Moore, McCabe & Craig: No new reading from the text today, but please finish reading material from Monday and Tuesday.
  • Optional reading: Chapter 5 of Exploratory Data Analysis with R, by Roger D. Peng. This text is available from the publisher at http://www.leanpub.com/ The publisher asks for a donation. If you select $0.00 for your donation, you get the text for free.


Thursday, June 30, 2016

  • Reading: Moore, McCabe & Craig: Pages 33-41.


Monday, July 4, 2016

  • No class: Independence Day!


Tuesday, July 5, 2016

  • Homework: Homework 6, I passed this homework out but no due date is assigned yet. Update: due July 13, 2016.
  • Reading: Moore, McCabe & Craig: Pages 42-67.


Wednesday, July 6, 2016

  • Reading: Moore, McCabe & Craig: Pages 67-72.


Thursday, July 7, 2016

  • Reading: Moore, McCabe & Craig: Pages 231-249.


Monday, July 11, 2016

  • Reading: Moore, McCabe & Craig: Pages 252-261.


Tuesday, July 12, 2016

  • Reading: Moore, McCabe & Craig: Pages 263-274.


Wednesday, July 13, 2016

  • Remember: Our exam tomorrow is in Anderson B-11 between 10 AM and Noon.


Thursday, July 14, 2016

  • Midterm Exam.


Monday, July 18, 2016

  • Extra Credit Assignment: Due Wednesday, July 20. Worth 10 points added to your homework score. You must be present in class on Wednesday, July 20 to get the points, and you must both participate in the discussion in class and turn in (on Wednesday) a short written paragraph describing your experience. Here is the assignment: Pick a topic, suggestions are below. See what data you can find on the web concerning this topic. Use Google, and start with the key words "data" and your topic. Are the data you find free or do they cost money? Can you download the data set or do you need a computer program (or hand copy) to pull them off the web? If you can download the data, can you load it into StatCrunch or do the data require "munging" to be used by StatCrunch? What are the cases, and what are variables? (If there are many variables, what are some of the ones that are of interest to you?) Spend at least 45 minutes on this assignment. If you finish with your first topic in less than 45 minutes, try another topic. Suggested topics (actually, whatever interests you): sports (of various kinds, there are lots of free good data on baseball), entertainment, movies (again good data), law, criminology, government, city planning, architecture, weather, climate, geology, seismology, medicine, epidemiology, health, fitness, biology, evolution, extinction, ecology, math, computer science, statistics, data science, anthropology, ethnic studies, gender studies, history, sociology, culture, tourism, archeology, art, literature, writing, journalism, census, linguistics, finance, economics, business, astronomy, physics, chemistry, library sciences, theology, anything else you can think of.
  • Reading: Moore, McCabe & Craig: Pages 81-107.


Tuesday, July 19, 2016

  • Review: The new material today concerns (1) sampling and (2) counting the number of samples of a certain size possible given the size of the population. The notes for this are in the most recent version of The Data Professor's Guide to Basic Statistics, pages 37-45.
  • Reading: No reading from Moore, McCabe & Craig today. Please read the material from the Data Professor's Guide linked to above, and complete the homework.
  • Extra Credit Assignment: Due tomorrow for class discussion. See July 18, above.


Wednesday, July 20, 2016

  • Review: We started to talk about inference today by examining a student project on the Philadelphia Eagles, team ranking and Quarterback salary. There are no materials to review here but we will discuss this more soon.
  • Review: Chapter 3. I sent the PowerPoint I used in class as an attachment to an email on Wednesday, July 20, 2016.
  • Homework: No new homework today.
  • Reading: Moore, McCabe & Craig, pages 168-174.
  • Extra Credit Assignment: Deadline extended until class time, tomorrow. We plan to continue our discussion, in class.


Thursday, July 21, 2016

  • Review: We continued our introduction to inference with a second example. Yesterday's example was a student project on the Philadelphia Eagles, team ranking and Quarterback salary. Today's new example was clustering trees in an old growth forest. You can read about this new example on page 352 of the textbook (Example 6.1).
  • Review: I presented a PowerPoint on section 2.2, 2.5, 2.7 of our textbook: Specifically, 2.2 (Scatterplots), 2.5 (Cautions about Correlations and Regression) and 2.7 (The Question of Causation) of the book. The PowerPoint is attached to an email sent July 21, 2016.
  • Homework: No new homework today.
  • Reading: Moore, McCabe & Craig, page 352, and sections 2.2, 2.5, and 2.7.


Monday, July 25, 2016

  • Review: We continued our introduction to inference with a third example: testing the null hypothesis that two proportions are equal, the proportion of patients that get better with a new drug under development versus the proportion of people who get better with a placebo. You can read about this example on pages 352-353 (Example 6.2).
  • Review: I completed the PowerPoint on chapter 3 that I started last Wednesday. The PowerPoint was attached to an email sent July 20.
  • Reading: Moore, McCabe & Craig, we covered pages 175-228 today. Please look over this material.


Tuesday, July 26, 2016

  • Review: We continued our study of tests of significance and started with confidence intervals.
  • Homework: There are no homework sets assigned today. Four were assigned yesterday and a due date was specified for a fifth that was already assigned. Please work on those.
  • Reading: Moore, McCabe & Craig, pages 351-390.


Wednesday, July 27, 2016

  • Handout: A brief lecture during this day's class concerned a handout about T Statistics.
  • Reading: Moore, McCabe & Craig, pages 301-316: Sampling Distributions.
  • Reading: Moore, McCabe & Craig, pages 417-441: T Statistics.
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