1. LISAM. Statistical software.
Lecture 2
Course leader: Oleg Sysoev
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2. LISAM What is LISAM? Social network for Creating personal pages
Creating courses
Storing course materials (lectures, documents, useful links)
Publishing assignments to certain student groups (labs, project work)
Uploading and submitting solutions to assignments electronically
Correcting and grading the solutions
Communication between students and teacher
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3. How it looks like when you logon
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4. Panels
Menu
Newsfeed: you find comments from people and courses you have chosen to follow
Important menus:
About me (edit the profile, set the default language)
Courses and Programmes: See all courses that you registered yourself for.
LISAM support help information
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5. If the webpage is in Swedish
About meUpdate profile
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6. Accessing a course
My courses
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7. Course structure
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8. Course structure
Syllabus: compressed information about the course, teaching, examination and admission requirements
Course documents: basic course material: lectures, files (uploaded by teacher)
Collaborative workspace: teachers and students can publish files there and make comments
Newsfeed: Teachers and students may start a conversation there
Announcements: information from teacher
Timetable: link to schedule in TimeEdit
Submissions: Here you may find your labs/assignments and submit the answer
Assessment record: The overview of your grades
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9. Course menus
Note that each lab/assignment has a deadline and an end date
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10. Submit a report
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11. Statistical, DM and ML software
Commerical
SAS
Minitab
SPSS
Matlab
Microsoft SQL Server
Free of charge: R
WinBugs, JAGS
Python
Apache Spark
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12. SAS
SAS
SAS Base
SAS Enterprise Guide
SAS JMP …
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13. SAS How SAS is started What is Library
Learn:
How SAS is started
What is Library
What's in the Editor, Output, Log
What's in the Results
How to create a library
How to import XLS document to the library
Note data material (Column attributes)
Write a simple computer program and save the file
proc. gplot data = sashelp.class;
plot height * weight;
run;
Run the program
Sas file upload.
Help (contents, index, search, SAS/GRAPH, SAS/STAT)
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14. R R is a computer language with full flexibility
Constantly increasing amount of packages (new research)
Free of charge
Website:
Code Editor:
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15. Software: use RStudio Install R: http://www.r-project.org/
Install RStudio:
Workspace
Program
Plots
Execution console
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16. Basics in RStudio Important to know:
Create a new file and save it (File menu)
Running one line or entire code (Edit menu)
Running one line in console
Workspace (Observe, Save, Clear)
Setting current directory (Tools)
Installing new package (Packages tabs)
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17. Call help Specific function Help browser Search for something in help
help(function)
Help browser
help.start()
Search for something in help
help.search(“expression”)
Quick reminder of function arguments:
args(function)
Examples of how to use function:
example(function)
If some method is not installed on the computer:
RSiteSearch(”expression")
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18. Introduction R is case-sensitive (A and a)
Each command on a new line or use ;
Comment:
#R is a very cool language!
Initialize/set the variable
Use-> or <- or =
a<-3
3->b
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19. Vectors
Create a vector
x<-c(1,3)
See the result x
print(x)
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20. Operation with vectors
indexing
Element-wise: +-*/^
log exp sin cos
length –number of elements
sum - sum of all elements
max min sort order
which.min which.max
Logicals:
TRUE or FALSE:
A=TRUE;
> >= < <= != & (and) | (or)
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21. Matrices Use matrix() a<-matrix(values,nrow=m,ncol=n)
Values should be listed columnvise
nrow= and ncol= can be skipped
Create empty matrix
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22. Matrix operations
Usual vector operations can also be applied:
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23. Matrix operations Matrix operators/functions: transpose b=t(a) b = aT
Inverse b = a-1
b=solve(a)
Solve d=a-1b
d=solve(a,b)
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24. Indexing for matrices Positive index x[1,6] x[2:10,] Negative index
x[2,-(1:5)] row 2 and all columns except 1:5
Entire column or row
y=x[2,] entire row 2
Extraction
x[x>5]
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25. Replication Replication for vectors Replication for matrices
rep(what, times)
Replication for matrices
matrix()
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26. Matrix operations Dimension Row/column stististics
dim(mat)
Row/column stististics
colMeans, rowMeans, colSums,rowSums
Apply a function over vector/matrix
Sapply()
Normally used when function works only element-wise
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27. Vector/matrix operations
Create confusion matrix (classification)
table(X,Y)
Extract diagonal
Diag(X)
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28. Factors
Text values
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29. Lists
List is a collection of objects
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30. Data frame
Vectors and matrices of the row length can be collected into a data frame
Used to store the data of different types into a single table
Use data.frame(object 1, object 2, … , object k)
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31. Data frame Any column in the data frame can be retrieved by
dataframe$object
Any row in the data frame can be extracted by using matrix notation, for ex: z[1,]
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32. Read data from Excel file
Save as ”comma-separated file”(csv)
Change current directory, Session Set Working Directory or setwd()
Use
Dataframe=read.csv2(file_name)
Dataframe=read.csv(file_name)
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33. Conversion between types
Data frame to matrix
Matrix to data frame
Numeric to factor
Factor to numeric
List to vector
Vector to list
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34. Conditioning and loops
If (x==3) { … } else { } for (i in 2:99) { while(x!=29) {
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35. Loops for (name in expr1 ) { … } while (condition) 732A60
Introductory course "Statistics & Data Mining" 2012

36. Using a function Use ?name_of_function to see function parameters
For ex. ?lm
There are some obligatory parameters and optional parameters
The optional parameters can be specified in different order
X=1:10
Y=1:10+rnorm(10)
W=c(rep(1,5), rep(2,5))
mydata=data.frame(X,Y)
result=lm(Y~X, weights=W,data=mydata)
?predict.lm
Fit=predict(result)
plot(X,Y)
points(X,Fit, type="l", col="blue")
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37. Writing your own functions
Function writing must always end with writing the value which should be returned!
You may also use ”return(value)” to show what value the function should return
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