Math 321 (Summer 2019)
Math 321 - Statistics for Experimentalists - Summer 2019
Syllabus
Daily Homework Assignments:
Here. *updated Weds 6/5
Course Notes:
These course notes will be updated from time to time. Check back often to get the most recent version. Under the chapter headings in each file will be a data indicating when the version was updated.
Chapter 1: Introduction, data, and basic statistics.
Chapter 2: Counting and probability
Chapter 3: Probability distributions (*updated 10/1/2019)
Chapter 4: Central limit theorem and sampling distributions. (*updated with brief summary page)
Central limit theorem and Students t-distribution notes and simulations
Chapter 5: Confidence intervals (*updated with brief summary page)
Chapter 6: Hypothesis testing (*updated with summary page and some minor corrections)
Chapter 7: Linear regression (*updated with minor changes and summary page)
Chapter 8: One-way ANOVA
Formula sheet (for exam 3 and final exam)
Statistical tables (for exam 3 and final exam)
Review materials:
Additional Chapter 2 counting review problems:
Problem set.
With solutions.
Additional Chapter 2 and 3 review problems on probability and distributions:
Problem Set.
With Solutions.
Additional Chapter 4 review problems on central limit theorem, law of large numbers, and sampling distributions:
Syllabus
Daily Homework Assignments:
Here. *updated Weds 6/5
Course Notes:
These course notes will be updated from time to time. Check back often to get the most recent version. Under the chapter headings in each file will be a data indicating when the version was updated.
Chapter 1: Introduction, data, and basic statistics.
Chapter 2: Counting and probability
Chapter 3: Probability distributions (*updated 10/1/2019)
Chapter 4: Central limit theorem and sampling distributions. (*updated with brief summary page)
Central limit theorem and Students t-distribution notes and simulations
Chapter 5: Confidence intervals (*updated with brief summary page)
Chapter 6: Hypothesis testing (*updated with summary page and some minor corrections)
Chapter 7: Linear regression (*updated with minor changes and summary page)
Chapter 8: One-way ANOVA
Formula sheet (for exam 3 and final exam)
Statistical tables (for exam 3 and final exam)
Review materials:
Additional Chapter 2 counting review problems:
Problem set.
With solutions.
Additional Chapter 2 and 3 review problems on probability and distributions:
Problem Set.
With Solutions.
Additional Chapter 4 review problems on central limit theorem, law of large numbers, and sampling distributions:
Problem Set.
With Solutions.
Additional Chapter 5 review problems on confidence intervals:
Additional Chapter 5 review problems on confidence intervals:
Problem Set.
With Solutions.
Additional Chapter 6 review problems on hypothesis testing:
Problem Set.
With Solutions.
Additional Chapter 7 review problems on linear regression:
Additional Chapter 7 review problems on linear regression:
Problem Set.
With Solutions.
Datasets:
Current Account balance data US and UK 1970-2017
Montana oil production data
Spokane Valley Well Depth
All US counties, selected demographic data on income, employment, race, and poverty
In class R histories:
M 5/20
T 5/21
W 5/22
M 6/3
W 6/4
M 6/10
T 6/11
W 6/12
M 6/17
T 6/18
W 6/19
M 6/24
Miscellaneous R code:
Coin flip simulation R code
usage:
> source("coinflipsim.R")
> flipcoin(N)
Poker simulation R code
usage:
> source("pokersim.R")
> drawManyHands(N)
Some cool sources for data:
World Bank
Google Data Explorer (good for viewing various datasets, but need to go tot he source to download the data)
St Louis Federal Reserve Bank
US Census Fact Finder
US Bureau of Labor Statistics
US Bureau of Economic Analysis
Data.gov
NOAA and NWS for climate and weather data
FBI crime data explorer
CDC mortality data
Online statistics learning resources
Statpages.info (a huge repository of resoruces)
Openstax (Basically very much like a proper textbook but online, seems easy to navigate, good basic examples)
Statlect (I really liked this one)
American Statistical Association statement on p-values
Common misinterpretations of the p-value and other statistical concepts
Guess the correlation game
Datasaurus dozen - shows how very different paired datasets can have the same scatterplot, and descriptive statistics
R statistical software:
You will need access to R statistical software. Here are instructions for getting R statistical software up and running on your computer. It should already be installed in all computer labs in Herak as well. If you find a computer where it is not installed, you can use these instructions to install it, or report it to me, and I will have IT install it.
Here is a website where you can evaluate R code online from your web browser from any device: https://rdrr.io/snippets/
Another option for having quick access to R (and this is useful for a smartphone) is SageCell at: https://sagecell.sagemath.org/. This website can be used to evaluate commands from a variety of programming languages (including MATLAB and Python). Just select R from the language tab at the lower right of the textbox. If you are familiar with MATLAB, choose the option "Octave". Octave is basically an open source version of MATLAB and you can run MATLAB code using the Octave language option on SageCell.
Datasets:
Current Account balance data US and UK 1970-2017
Montana oil production data
Spokane Valley Well Depth
All US counties, selected demographic data on income, employment, race, and poverty
In class R histories:
M 5/20
T 5/21
W 5/22
M 6/3
W 6/4
M 6/10
T 6/11
W 6/12
M 6/17
T 6/18
W 6/19
M 6/24
Miscellaneous R code:
Coin flip simulation R code
usage:
> source("coinflipsim.R")
> flipcoin(N)
Poker simulation R code
usage:
> source("pokersim.R")
> drawManyHands(N)
Some cool sources for data:
World Bank
Google Data Explorer (good for viewing various datasets, but need to go tot he source to download the data)
St Louis Federal Reserve Bank
US Census Fact Finder
US Bureau of Labor Statistics
US Bureau of Economic Analysis
Data.gov
NOAA and NWS for climate and weather data
FBI crime data explorer
CDC mortality data
Online statistics learning resources
Statpages.info (a huge repository of resoruces)
Openstax (Basically very much like a proper textbook but online, seems easy to navigate, good basic examples)
Statlect (I really liked this one)
American Statistical Association statement on p-values
Common misinterpretations of the p-value and other statistical concepts
Guess the correlation game
Datasaurus dozen - shows how very different paired datasets can have the same scatterplot, and descriptive statistics
R statistical software:
You will need access to R statistical software. Here are instructions for getting R statistical software up and running on your computer. It should already be installed in all computer labs in Herak as well. If you find a computer where it is not installed, you can use these instructions to install it, or report it to me, and I will have IT install it.
Here is a website where you can evaluate R code online from your web browser from any device: https://rdrr.io/snippets/
Another option for having quick access to R (and this is useful for a smartphone) is SageCell at: https://sagecell.sagemath.org/. This website can be used to evaluate commands from a variety of programming languages (including MATLAB and Python). Just select R from the language tab at the lower right of the textbox. If you are familiar with MATLAB, choose the option "Octave". Octave is basically an open source version of MATLAB and you can run MATLAB code using the Octave language option on SageCell.