You should work on this quiz on your own and not get help from others. You are however, encouraged to use the web and any other reference materials and resources to complete these questions. All the bulleted parts count an equal amount of points.
To make it easy to work this quiz all data sets are included in the APPM2720 Quiz directory. They are also in the dataWorkshop package and also have been posted in the Week3 class folder
Please submit your work to me by email email@example.com before class on Monday February 1, 2016. You can submit your answers:
(1) Load the data set BoulderJuneTemperature ( in
BT.rda) create a working data set:
BTfrom Fahrenheit to Centigrade and create a new data
BTand the mean of the new data set? What about the maximum values of each data set?
(2) Load the data set
This is a data frame of monthly mean temperatures from 1897 through 2014).
Recall that to extract the "year" variable you can use
yearLabel<- row.names(BoulderTemperature) Year <- as.numeric(yearLabel)
Make a plot of the these summer values over time and comment on whether you see a trend in temperatures (perhaps due to global warming). Be sure to label and title your plot.
(3) In R to find the missing values (NAs) in a data set you can use the
is.na function to create a data set of TRUE/FALSE values where TRUE means the original values was missing.
test<- c( 1,3,4.5, NA,10) ind<- is.na(test) sum( ind)
Will give you the number of missing values in a the data set test.
applyfunction for the
BoulderTemperaturedata report the number of missing values for each month.