Author: Leonore Findsen, Qi Wang, Sarah H. Sellke, Jeremy Troisi

Transcription

1 0. Downloading Data from the Book Website 1. Go to 2. Click on Data Sets 3. Click on Data Sets: PC Text 4. Click on Click here to download. 5. Right Click PC Text and choose Extract All. Be sure to place them somewhere where you can find them. The following is where I store all the files: Please remember how your files are stored so that you can access them for the labs. 1. General Information for R a) R uses functions to perform operations. To run a function with two inputs called funcname, we type funcname(input1, input2). 1

2 b) There is online help that is available. All you need to do is type? command at the > /command prompt and your browser will open up with a help file. For example,?setwd at the > prompt will open the available help documentation on utilizing the setwd() function. I also find that google is very effective if you are confused about a command. c) The # symbol/sign indicates a comment in R, i.e. everything to the right of the # sign will NOT be run as code. d) Capitalization is important. e) If you are more experienced, I suggest that you use scripts rather than typing in all of the commands at the prompt. To open a script, when the R console is open, go to File New script. To run a script, select what part of the script that you want to run and click on in the menu. Another method to running a script is by placing your cursor at the beginning of the first line of code that you wish to run, then pressing CTRL + r will run that line of code. The cursor will automatically move down one line. If you want to run multiple lines, you may repeat this process. Also, you may use RStudio which is also available. We will not provide written tutorials for these alternative methods but the instructors and TAs can help you with them in class or office hours. 2. Importing Data sets and printing them. Hummingbirds and flowers. (Data Set: ex01 88helicon.txt) Different varieties of the tropical flower Heliconia are fertilized by different species of hummingbirds. Over time, the lengths of the flowers and the form of the hummingbirds beaks have evolved to match each other. Here are data on the lengths in millimeters of three varieties of these flowers on the island of Dominica: 2

3 This data set comes from the textbook because it starts with ex (exercise) or eg (example). If the data set does not come from the book, there will be statement indicating where the data set can be found. For data sets that come from the book, the chapter number is next which indicates which directory to look under, followed by a dash and then the exercise or example number. In R, you will need to know the directory that you have saved your files into. If you do not know that, you may use the menu to change your default directory to the appropriate one by: File Change dir. (OPTIONAL) An alternative method is to utilize the setwd() command appropriately: >dir < getwd() >#Modify the path of dir to where your files are stored. >#i.e. dir < c:/stat350 >setwd(dir) To make sure helicon is in your working directory, utilize the following command: >ls() This will list all the R objects that you have in that particular R session/directory. (REQUIRED) Once you have set your directory to where the data file is stored, you will be able to read in the data that is stored in that directory without mentioning the directory path in the command. The command to read in your data is as follows: >helicon < read.table(file="ex01 88helicon.txt", header=true) I am assuming that the default directory has the file ex01 88helicon.txt. We have a second argument header = TRUE to indicate that the first line of the text file contains the names of the variables. All of the files that we are using will be of this format. More arguments are needed if there are spaces in the header line. This will be discussed later. Please name your table in context. In this case, we are interested in Heliconia flowers, so I named the table helicon. Since capitalization is important, I often only use small letters. If you want to put a space in the name, use an underscore, _. >helicon This line will print out the entire data set. This is not required, but I strongly recommend that you include it. I look at this output when the answer doesn t look right or I want to know what the variables are called (see below). If this output is not what is provided (or what is in the.txt file), then you are not reading in the information into the program correctly. Please do NOT turn in the output from this code. 3

4 (OPTIONAL) Assuming that helicon is in your current R session, run the following commands below and observe their outputs. Do not worry if you do not understand the output from each line as we are only currently attempting to build familiarity to R at this point in time. >head(helicon) >tail(helicon) >helicon[20:30, ] >names(helicon) >dim(helicon) >attach(helicon) >length(helicon[, 2]) >class(helicon) >class(helicon[1, ]) >class(helicon[, 2]) >class(helicon[, 1]) >levels(helicon[, 1]) >sum(helicon[, 2]) >summary(helicon[, 2]) >tapply(helicon[, 2], helicon[, 1], summary) >sd(helicon[, 2]) >sort(tapply(helicon[, 2], helicon[, 1], sd)) >subset(helicon, subset = helicon[, 1]!= red ) 3. Creating Histograms a) Create a histogram for the length of all of the flowers. You will need to tell R the variable of interest from the table that was read in. There are three ways to do this: 1) >attach(helicon) Then cite by the variable name alone as listed in the R object helicon itself. Note when using the attach command, the names of the R object's variables have to be different than the name of the variables in your global environment including the current R object itself. 2) use the order in which the variables occur in square brackets after the R object 3) use the variable name following a $ sign after the R object In this example, we are interested in the variable Length which is the second variable. Therefore, you would indicate it by Length, helicon[, 2], or helicon$length, respectively. I personally prefer the first method, so long as it is the main R object of interest as only one R object can be attached at a time. If this is not the case, I prefer the third method. You can use the output >heliconto determine what the variable names are (or from the.txt file itself). There are other methodologies which can be used which will be mentioned in later tutorials. 4

5 The methodology to create the histogram is: 1) >attach(helicon) >hist(length) 2) >hist(helicon$length) 3) >hist(helicon[, 2]) (OPTIONAL) We will be discussing additional options for creating histograms in later tutorials, such as utilizing the lattice graphics package that can be installed from within an R session: >install.packages( lattice ) #Only needs to be run once >library(lattice) #Needs to be run for each and every R session >histogram(~helicon[, 2]) (REQUIRED) Plots from 2) and 3) are shown below: 5

6 I would strongly suggest that you reduce the size of the plots so that more than one will fit on a page. 6