Math 321-04 (Spring 2022)
Statistics for Experimentalists, Spring 2022, Math 321-04
*See Blackboard for the syllabus, assignments, course notes, datasets and other course materials*
*See Webwork for regular homework assignments.*
*This GU Connect website will also be used for posting various course materials and information.*
R statistical software:
Getting/accessing R 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.
Learning R software:
I will supply course notes that will be fairly comprehensive on how to use R & RStudio.
Here is a great collection of R & RStudio cheat sheets: https://www.rstudio.com/resources/cheatsheets/
Here are probably the most useful ones for beginners:
Basic R: https://github.com/rstudio/cheatsheets/blob/main/base-r.pdf
RStudio IDE: https://raw.githubusercontent.com/rstudio/cheatsheets/main/rstudio-ide.pdf
Here is a very comprehensive instructional textbook on R: https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf
Here is another nice website with basic R lessons: http://www.r-tutor.com/r-introduction
Scanning work for turning in:
When turning in scanned work via email or to Blackboard, please:
- convert it into a single high resolution pdf document (per assignment),
- make sure all text is legible,
- make sure the pages are oriented correctly and in a standard page size, and
- each page has a margin or a similar amount of empty space for any comments I might leave.
This will make it easiest for me to keep everything organized and to write comments on the work to send back to you.
CamScanner is an app that I use to scan from phone to pdf. You can take multiple pictures and it will output a single pdf. It's available for both Android and iPhone. There are many similar apps; Android and iOS probably have built-in stock solutions as well. Some apps will leave a watermark if using free versions, and that's fine (as long as it doesn't cover up anything important).
If you have a local scanner, that should work too. I prefer 300dpi and color, but 150dpi and black-and-white/greyscale may suffice. Please check your pdf document so that the work is legible. Sometimes small writing or light writing (such as soft pencil) doesn't scan well. I suggest using blue or black ink or a sufficiently dark pencil for your written work. You could even try photos of boardwork, but make sure to organize it into a single document (per assignment).
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 Data
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
UCI Machine Learning Repository
World Population Review
Our World in Data (for good analysis/graphics and links to course data)
Visual Capitalist (for very nice graphics and links to course data)
Online statistics learning resources:
Statpages.info (a huge repository of resources)
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
Spurious correlations
*See Blackboard for the syllabus, assignments, course notes, datasets and other course materials*
*See Webwork for regular homework assignments.*
*This GU Connect website will also be used for posting various course materials and information.*
R statistical software:
Getting/accessing R 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.
Learning R software:
I will supply course notes that will be fairly comprehensive on how to use R & RStudio.
Here is a great collection of R & RStudio cheat sheets: https://www.rstudio.com/resources/cheatsheets/
Here are probably the most useful ones for beginners:
Basic R: https://github.com/rstudio/cheatsheets/blob/main/base-r.pdf
RStudio IDE: https://raw.githubusercontent.com/rstudio/cheatsheets/main/rstudio-ide.pdf
Here is a very comprehensive instructional textbook on R: https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf
Here is another nice website with basic R lessons: http://www.r-tutor.com/r-introduction
Scanning work for turning in:
When turning in scanned work via email or to Blackboard, please:
- convert it into a single high resolution pdf document (per assignment),
- make sure all text is legible,
- make sure the pages are oriented correctly and in a standard page size, and
- each page has a margin or a similar amount of empty space for any comments I might leave.
This will make it easiest for me to keep everything organized and to write comments on the work to send back to you.
CamScanner is an app that I use to scan from phone to pdf. You can take multiple pictures and it will output a single pdf. It's available for both Android and iPhone. There are many similar apps; Android and iOS probably have built-in stock solutions as well. Some apps will leave a watermark if using free versions, and that's fine (as long as it doesn't cover up anything important).
If you have a local scanner, that should work too. I prefer 300dpi and color, but 150dpi and black-and-white/greyscale may suffice. Please check your pdf document so that the work is legible. Sometimes small writing or light writing (such as soft pencil) doesn't scan well. I suggest using blue or black ink or a sufficiently dark pencil for your written work. You could even try photos of boardwork, but make sure to organize it into a single document (per assignment).
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 Data
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
UCI Machine Learning Repository
World Population Review
Our World in Data (for good analysis/graphics and links to course data)
Visual Capitalist (for very nice graphics and links to course data)
Online statistics learning resources:
Statpages.info (a huge repository of resources)
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
Spurious correlations