Information Processing II

Goal of the Course:

This course introduces students to basic understanding on data processing and some software tools commonly used for information processing in the area of Social Studies and Business Management. Course enrollment for this class is based on Information Processing I class.

Standards for Achieving Goal:

Basic understanding on Information Processing and develop solution to Data-processing related problems by using either the existing software, creating new programs with programming languages, or interfacing the program to existing software applications. Creating and maintaining a database using either Visual Basic or C programming languages: searching, sorting, filtering, hiding data, and report generation in windows-based environments.

Statistical data processing:
Simple statistical analysis (Sum, Average, Max/Min, Standard Deviation, Rank, Mode, Median, Frequency . . . etc.), Hypothesis testing, correlation analysis, simple regression, multiple repression, time series analysis, and practical use of SPSS software tool.

Teaching Methods:

Practical training in the Information Processing Classroom.

Prerequisite:
A good grade (B or better) in Information Processing I, and basic knowledge/background on Mathematics.

Overview of Each Class:

Class 1. General overview and basic concepts of computer programming. In this class, students will learn C programming in contrast to VB programming they learned from the previous semester. Element of programming (constants, variables, and strings) in C will be introduced in a simple program. Error trapping and debugging facilities available in C will also be demonstrated.

Class 2. Flow control structures (decision structure and loops), and structured programming concepts will be taught at this class time. Programming development cycle, flowchart, pseudo code, and algorithm will be used to describe the design process in C programming. A simple program with function and procedure subroutine in C will be demonstrated.

Class 3. This class will discuss on file/transaction processing cycle (data capture or data entry, data processing and report generation) which is commonly found in Data Base Management Systems and Management Information System (MIS) Projects. Students will practice on how to run a sequential file input and output(s) using C language.

Class 4. Starting from this class up to Class 8, students can use either C language or VB language for their program implementations. In this class, the difference, and advantage vs. disadvantage between sequential file and random access file will be discussed. A random access file with encryption/decryption methods (to hide important secret data base) will be demonstrated for entering, modifying, and simple processing on record-type of data.

Class 5. This class will discuss on searching, sorting, filtering data, and report generation /printing. A program that sorts and filters data, based on certain field(s) with certain criteria (using array type of data) will be used as an example.

Class 6. Students will learn an advanced technique in programming and create a program with several objects (ActiveX controls). A small program that connects C or VB program to MS-Access database (*.mdb) file(s) will be demonstrated to search, modify, add or delete records of data.

Class 7. Interfacing between C or VB program to MS-Office Application package has many advantages to solve complicated programming processes. A program that connects to MS-Word for spelling check and to MS-Excel for financial functions (calculating interest payments) will be demonstrated.

Class 8. In this class, students will learn how to run and write a program with objects of audio (*.wav), image, and video (*.avi) files, which is commonly found on a CDROM nowadays.

Class 9. Statistical package. This class will introduce students to basic statistical processing: frequency, mean, average, standard deviation and error using SPSS software package. Students can also use this package for presentation of data with bar chart, pie chart, curve, or any other graphical methods.

Class 10. Statistical package. This class will continue with the application of statistical package for Hypothesis Testing (comparing the average) on two groups of data, t-test, and goodness of fit test.

Class 11. Statistical Package. Students will learn and practice on Correlation Analysis: correlation and cross correlation coefficients (to measure the correlation between two or more variables), rank correlation, and scatter diagram.

Class 12. Statistical package. This class will discuss the basic usage of SPSS for linear regression to calculate the regression line (equation) between dependent variable and independent variable. Variable transformation, standard error, and predicting dependent variable based on estimated independent variable will also be presented.

Class 13. Statistical package. Calculating multiple regression with SPSS: correlation matrix, multiple regression equation, regression coefficient, dummy variable, and selecting the best regression equations.

Class 14. Statistical package. Students will study on time series analysis: exploring data pattern on stock price data with autocorrelation coefficient, smoothing methods, forecasting techniques, and measuring the forecasting error.

Class 15. Reviews. Overview on recent software tools for data processing and general review of all classes.


Method of Grade Evaluation:

Attendance 35%
Mid term tests 15%
Term Papers 10%
Final Paper 25%
Participation 15%

Requirements for Students:

Students are suggested to bring their own ZIP-disk (Windows compatible type 100 MB) and FD disk (3.5 inches 1.4 MB). Those who have some advanced knowledge of computers are allowed to register.

The following should be noted when entering Information Processing Classrooms:

(1) Do not bring in any food or drinks.
(2) Do not smoke inside the classroom.
(3) Do not bring any wet umbrellas or coats.
(4) Turn off cellular phones. (if possible, do not bring them in.)
(5) Do not use cosmetics.
(6) Do not leave any trash on the computer desk or in the classroom.
(7) Do not talk loudly.
(8) Other activities that may disturb others or harm the computer-equipment are prohibited.

Students who violate these rules can be denied permission to enter the classroom.


Suggested Reading:
1) Hary Gunarto, Learn Visual C++ for Information Processing, Andi Offset Pub., 2002.
2) Beck Zaratian, Microsoft Visual C++ 6.0, Microsoft Press, 1998.
3) Michael Halvorson, Learn Microsoft Visual Basic 6.0 Now, Microsoft Press, 1999.
4) Samuel B. Green, Neil J. Salkind, Theresa M. Akey, Using SPSS for Windows: Analyzing and Understanding, Prentice Hall, Second Edition, 2000.


Internet Website related to the course:
http://msdn.microsoft.com/vba/
http://www.microsoft.com/officedev/
http://www.microsoft.com/workshop/author/dhtml/edit