r for statistical data analysis

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Workshop: R for Sta/s/cal Data Analysis-‐an alterna/ve to SPSS. UiTM 26 April 2016 . Dr. N Ahmad

25 April 2016 !Dr. Norhaiza Ahmad!

Department of Mathematical Sciences!Faculty of Science!

Universiti Teknologi Malaysia!

R for Statistical Data Analysis!

an Alternative to SPSS!!

PART A0: R INTRO!



Outline

● PART A: INTRO § What is R §  History § Why Use R vs SPSS (or other commercial packages) §  Types of R §  Downloading & Installing R (see aMach) §  Execu-ng & Running R Commands §  Saving and QuiRng R



What is R?

•  A computer language, with orientation towards statistical applications

•  Growing rapidly in use



History

•  R programming language is an offshoot of a programming language called S.

•  Splus •  Commercial ware •  S Plus (1988) vs. R (1993)



Why Use R?

•  FREE! •  Well documented-many add-on packages for

specialized uses •  We can inspect the actual codes and modify

to our needs •  Has a large community of R users online who

can answer your questions and who contribute to ‘packages’ in R

•  Minuses –  Obscure terms, in-mida-ng manuals, odd symbols, inelegant output (except graphics)



R •  Many different datasets (and other “objects”) available at same -me

•  Datasets can be of any dimension •  Func-ons can be modified •  Experience is interac-ve-‐you program

un-l you get exactly what you want •  One stop shopping -‐ almost every

analy-cal tool you can think of is available

•  R is free and will con-nue to exist. Nothing can make it go away, its price will never increase.

•  One datasets available at a given -me •  Datasets are rectangular •  Func-ons are proprietary •  Experience is passive-‐you choose an

analysis and they give you everything they think you need

•  Tend to be have limited scope, forcing you to learn addi-onal programs; extra op-ons cost more and/or require you to learn a different language (e.g., SPSS Macros)

•  They cost money. There is no guarantee they will con-nue to exist, but if they do, you can bet that their prices will always increase

SPSS/Other Canned Packages



R vs. SPSS

Product Developer Latest Version Open Source

Cost

R R Foundation April 14, 2016 Y None

SPSS IBM March 15, 2016 N $$$$$

https://en.wikipedia.org/wiki/Comparison_of_statistical_packages



Recommended Books

ISBN 978-‐0-‐387-‐09418-‐2 ISBN-‐13: 978-‐1420079333



Types of R

•  R command line (very liMle interface) •  R with menu-‐driven interac-ve interfaces: •  R commander •  R studio

•  We will use this. •  Develop

programming skills that can be carried over for the other R.

R has currently different packages to work with: Deducer The R commander JGR SciViews pmg Rkward, for KDE Cantor, which integrates R, Latex, Sage, Maxima and KAlgebra



R

Downloading & Installing base R



GeVng Started: Downloading R

•  Internet connec-on • See step by step procedure on how to download R

• End up with R icon on desktop



hWp://www.r-‐project.org/



Downloading Base R [Figs 1.1 – 1.4]

•  Click on Windows •  Then in next screen, click on “base”

•  Then screens for Run, OK, or Next

•  And finally “Finish” –  will put R icon on desktop When you download

and install R, you are downloading and installing base R and selected packages.



R

How to Run & Execute R commands?



How to Run commands in R: Method 1: R Console

R prompt (>)

R is updated regularly. Check the R version on your PC

At the R prompt: -‐Type your R commands here!

•  Computa-ons are performed on an R console •  R commands are

typed and evaluated here.



> 6+3 > 6-3 > (22+ 18+35)/3 > 31 %% 7

R as calculator

•  Write your R commands aser each prompt •  Hit Enter to execute command

•  Other operators: +, -‐, *, /



Handy Tip

•  Recall the previous R commands used by using the up and down arrow keys.



Making Comments in R

•  Comment lines in R are denoted by “#” •  Any lines that is wriMen aser “#” will not be read as an R command

•  Comment lines are useful for making nota-on/notes in your program

> 31 %% 7 #remainder after division of 31 by 7. ie. 31(mod 7)



Script window

A script: separate window where you can type your commands and run them at your own convenience.

It is similar to a notepad/text file!

At the ribbon: File -‐ New

How to Run commands in R: Method 2: R Script



Wri/ng in an R Script File

# ======== # 20 Nov 2014 # This is my first R document # ======== 6+3 6-3 6+3; 6-3

Step 2: To run commands in a script file: Highlight all the commandsà Right Click à Choose Run line or selec/on

NOTE: Use semi colons to separate different command lines 6+3; 6-‐3

Step 1: Type these. There is no “>“ prompt in a script file

Step 3: Save your script file in your D drive. è similar to saving a notepad/text file



R Assignment

> # use ‘=‘ or ‘<-’ for assignment > x <-2 > x > x <-2 > x

R is object oriented program. Each input/output can be assigned/ stored to an object

•  Once an R object is assigned, it can be called upon at any -me as long as it is saved. Here the number 2 is stored in an object called “x”.

•  In general, R objects are stored in an R workspace, also known as the global environment.



R Assignment

> # Use ‘;’ to combine line commands > x <-2; x > len = 2; len

•  Once an R object is assigned, it can be called upon at any -me as long as it is saved. Here the number 2 is stored in an object called “x”.

•  In general, R objects are stored in an R workspace, also known as the global environment.



R Assignment

> # Use ‘()’ to auto call up assignment > (x <-2) > (len = 2) • TIP: Use brackets around assignment – to automa-cally call up stored variable



Important Rules

1.  We created a variable/ object name 2.  Variable names are case sensi-ve 3.  No blanks in name

(can use _ or . to join words, but not -‐) 4.  Start with a leMer (capital or lower-‐case) 5.  Can use <-‐ instead of =



Handy Tip

•  If a command is not complete at the end of a line then R will issue the following prompt (by default):

+ •  on second and subsequent lines un-l the command syntax is correct. To break out of this, type CTRL + c (press the Control Key and ‘C’ at the same -me).



Example

Suppose the compound interest based on an interest rate of 0.25% per year of a 30 year period is 1.078. Calculate the bank balance aser 30 years, if the ini-al balance is RM3000. Op-on 3 Recommended. Occasionally it may be

convenient to use Op-on 1 or Op-on 2 > Ir.30= 1.078 > I.bal= 3000 > (F.bal= I.bal*Ir.30)



FUN Tips!

•  You can change the appearance of your prompt symbol ‘>’ to some other form:

> op-ons(prompt = "R> ") To return to the default prompt: > op-ons(prompt = "> ")



Saving Stuff

① You can save individual variables with the save() func-on.

② You can save the en-re workspace with the save.image() func-on.

③ You can save your R script file, using the appropriate save menu command in your code editor.

Op-on 3 Recommended. Occasionally it may be convenient to use Op-on 1 or Op-on 2



Saving Stuff

•  To exit: •  hit X (top right corner) or at R prompt > quit ( ) •  Brings up to this screen: •  Unless you need to recall certain objects

regularly, we do not need to save the workspace .

•  Thus, make it a prac-ce to save your work on a script file instead.

•  Workspace is your current working environment. This includes all the func-ons, objects etc that you have created in that session.



References

•  Slides adapted from T. P. Hogan, A Brief Introductory Guide, SAGE Publica-ons, 2010

T. Mar-n, The Undergraduate Guide to R W. J. Braun et al, A First Course In Sta-s-cal Programming with R (2008)

Other ways to learn R: hWp://swirlstats.com/



NEXT

● Exercises ● PART A1: Func-ons, Packages & Help in R

r for statistical data analysis

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