Upon grading the labs I noticed there is interest in adding color to the plots. I understand and appreciate the desire to make your figures more aesthetically pleasing. I have used colors to make the figures fit the overall style of whatever publication they are going to be used in. However, my general advice is to only use color when it adds value. For example, coloring bars or points based upon a quantitative variable is often very helpful.
To explore how R generates randome numbers, we will use the rnorm function. This function draws a random number from a normal distribution with a mean = 0 and standard deviation = 1 (though these can be changed with the mean and sd parameters). With n = 1 we will get two random numbers. rnorm(n = 1) ##  0.4766584 rnorm(n = 1) ##  0.07708628 Each time you run the command you will get a different number.
To get started with the labs, you will need to install R and other supporting applications. Links to download all the software is on the Software page at http://data606.net/software which is available on the Course Overview menu. Once you are in RStudio, you will need to install a number of R packages using the following two commands: install.packages(c('openintro','OIdata','devtools','tidyverse', 'ggplot2', 'psych','reshape2','knitr','markdown','shiny','R.rsp', 'fivethirtyeight')) devtools::install_github("jbryer/DATA606") Note that this course used to be listed as IS 606, hence the different package name.
Welcome to DATA606! My name is Dr. Jason Bryer and I will be your instructor for this semester. In addition to teaching this course, I am Principal Investigator of a Department of Education grant to develop a Diagnostic Assessment and Achievement of College Skills (see www.DAACS.net for more information) and a Research Data Associate at Cornell University. Couple of important notes as you get started: The course syllabus located here: https://spring2020.