These are R programming assignments.

1. Make sure that your class has several named objects stored in the memory of R. You can have them create a few simple data items as practice. 2. Use the Is() command to view a list of named objects in R's memory. 3. Show how to use pattern matching to refine the list of named objects when using the Is() command. 4. Look at removing objects using the rm() command. Note that objects so removed are deleted. 5. Introduce your class to the difference between numbers and text and how to convert from one to the other. 6. R recognizes different kinds of objects; show your class these different objects: vector, data frame, matrix and list. 7. Look at the structure of data objects using the str() command. 8. Now use the class() command on a variety of objects to see what kind they are. 9. Show how to save objects to disk using the save() command. 10. Show how to save everything using the save image() command. 11 Show how the bieterv af reviews Submit Assignment Dashboard Calendar To Do Notifications Inbox 11. Show how the history of previous commands can be accessed using the arrow keys. 12. History files can be saved to disk (and of course loaded from disk). Demonstrate how to do this using the savehistory() and loadhistory() commands. You might also like to create a list of commands as a plain text file using a text editor and use the loadhistory() command to load it into R (this could also be a homework activity). 13. Use the load() command to load a file from disk. You could use the Beginning. RData file as an example; this loads lots of data objects into R, which you can use in later exercises. 14. Show how to save a simple data object to disk using the write() and cat() commands. 15. Now show how to save data frames and matrix objects as plain text using the write.table() command and variants such as write.csv() for saving CSV files. 16. Use the dout() and dget() commands to save and load a text representation of a list object. 17. If you have time you can end with an illustration of how to deal with list items. 16. Use the dput() and dget() commands to save and load a text representation of a list object. 17. If you have time you can end with an illustration of how to deal with list items, which are generally useful but harder to deal with. You might like to get your class to read the relevant section for themselves and practice converting a list to a data frame before the next exercise