Emre Ugur

Ph.D.

CMPE140 Introduction to Computing for Economics and Management
2017-2018 Fall


Aim:
CMPE 140 introduces basic concepts of computing with the R programming language. Course topics include an introduction into basic data structures (vector, matrix, lists, data frames, etc.), program control statements (conditional execution, for and while loops, etc.), data visualization and input/output.
Instructor: Emre Ugur (contact)
Teaching Assistants: Mert Tiftikci (CMPE), Serhat Cevikel (AD)
Office hours: Anytime. Drop a line before coming to my office (BM33)
Lecture notes and all communication is through Piazza. Please send email if you are not registered!

Timetable:

Lecture Wednesday 13:00-15:00 New Hall Building, Room NH405
Problem Session Wednesday 15:00-16:00 New Hall Building, Room NH405
Lab for CMPE104.1 Friday 13:00-15:00 CMPE Building, Room B4
  • Lab for CMPE104.2
    		• Friday 15:00-17:00 CMPE Building, Room B4


    Schedule:
    TimeChapterTopics
    20.09.2017 Introduction
    • Course objectives and organization,
    • R Intro,
    • R Download and Installation,
    • Simple calculations,
    • R help and documentation,
    • R Programming Environment,
    27.09.2017 Vectors
    • Variable name conventions
    • Creating data vectors
    • Data vector indexing
    • Data vector filtering
    • Data vector sorting
    • Data vector operations
    • Creating regular sequences
    • Creating repeated values
    04.10.2017 Matrices
    • Matrix creation
    • Matrix modification
    • Matrix operations
    • Matrix indexing
    • Matrix filtering
    • Matrix function apply()
    • Programming own functions
    • Higher-dimensional arrays
    11.10.2017 Lists
    • Shortcomings of vectors and matrices
    • Creating lists
    • List indexing
    • Adding/deleting list elements
    • Concatenate lists
    • Vectors as list components
    • Example: word list
    • Accessing list components/values
    • Example: sort word list alphabetically
    • Applying functions to lists
    • Example: sort word list by word frequency
    18.10.2017 Data frames
    • Shortcomings of vectors and matrices
    • Creating data frames
    • Accessing data frames
    • Data frame indexing
    • Data frame modifications
    20.10.2017Midterm!
    25.10.2017 Loops
    • Data import from file
    • Data frame summary
    • Scatter plot
    • The for-loop
    • Print variable when iterating
    • Compute length/norm of a vector
    01.11.2017 Loops continued
    • Square elements of a vector
    • Function findwords
    • Read data from file
    • if-else statement
    • Plotting word frequencies from Wikipedia articles
    08.11.2017 Loops continued
    • Nested loops
    • While loop
    • Print vector elements when looping
    • Compute length/norm of a vector
    • While vs. for loop
    • Break statement
    • Quiz with the while loop
    • Random numbers with the while loop
    • Repeat loop
    • Next statement
    15.11.2017 Graphics
    • Scatter plot
    • Barplot
    • Scatter plots of data frames
    • Histograms
    • Figure arrays
    • Scatter plot vs. Histogram
    22.11.2017 Graphics Continued
    • Boxplots
    • Stripcharts
    • Pie charts
    • Word frequency
    • Caffeine consumption and marital status
    • Sales data
    29.11.2017 Input and Output
      • Read data with scan
      • Read from the keyboard
      • Read into a matrix
      • Reading text files
      • Accessing files from the Internet
      • The UCI Machine Learning Repository
      • Iris flower data set
      • Word frequencies of ebooks from Project Gutenberg
      • Export graphics
      • Writing to files
    06.12.2017 Data analysis
    Wrap-up
      • Data structures
      • Conversion between data types
      • Correlation and dependence
      • Linear Regression
      • Prediction
    13.12.2017 Summary for final exam

    Grading:
    • Lab session (quiz) : 30 %
    • Midterm : 25%
    • Final : 45%