Apply to USF Now | Graduate Admissions | Events & Workshops | Giving to the Office of Graduate Studies

Graduate Course Proposal Form Submission Detail - ISM6137

Edit function not enabled for this course.


Current Status: Approved by SCNS - 2012-04-09
Campus: Tampa
Submission Type: New
Course Change Information (for course changes only):
Comments: to GC; pndng cat/concur- CSE, Math. for Finance Prog Changes (apprd 11/14/11); to GC 11/28/11. Rev. Obj . Emld fac 1/13/12. OKd. To GC 2/6/12; 2/20/12. Appd. To USF Sys 2/20/12. to SCNS 2/28/12. Appd eff 4/15/12. Banner. Subm 6830. Appd as 6137


  1. Department and Contact Information

    Tracking Number Date & Time Submitted
    2626 2011-09-19
     
    Department College Budget Account Number
    Information Systems and Decision Sciences BA 1407000
     
    Contact Person Phone Email
    Kaushal Chari 8139746768 kchari@usf.edu

  2. Course Information

    Prefix Number Full Title
    ISM 6137 Statistical Data Mining

    Is the course title variable? N
    Is a permit required for registration? N
    Are the credit hours variable? N
    Is this course repeatable?
    If repeatable, how many times? 0

    Credit Hours Section Type Grading Option
    3 C - Class Lecture (Primarily) R - Regular
     
    Abbreviated Title (30 characters maximum)
    Stat Data Mining
     
    Course Online? Percentage Online
    C - Face-to-face (0% online) 0

    Prerequisites

    one course in basic statistics or equivalent

    Corequisites

    none

    Course Description

    Development of statistical concepts and methods for mining large business data bases


  3. Justification

    A. Please briefly explain why it is necessary and/or desirable to add this course.

    Needed for new program/concentration/certificate

    B. What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service?

    50 students year

    C. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times?

    No

    D. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.)

    Ph.D. in Statistics or related field.


  4. Other Course Information

    A. Objectives

    1 To learn methods and concepts related to statistical modeling and statistical data mining 2 To understand when to use a particular method and to learn about its limitations 3 To implement methods and concepts on real data using state of the art software

    B. Learning Outcomes

    1 To learn methods and concepts related to statistical modeling and statistical data mining 2 To understand when to use a particular method and to learn about its limitations 3 To implement methods and concepts on real data using state of the art software

    C. Major Topics

    Introduction Regression Basics Statistical Inference for Regression Deviations from the linear model and modeling alternatives Collinearity Principal Components and Variable Selection Flexible methods for large data sets Nonparametric Regression and Regression Trees Methods for Time and Spatially Dependent Data Methods for combinations of cross sectionaql and time or spatially dependent data Functional Data Analysis Methods for non continuous response data Logit and Choice Models Methods for hierarchical data Linear Mixed Models Hierarchical Models

    D. Textbooks

    Jank Business Analytics for Managers Springer 2011 ISBN 978 1 4614 0405 7

    E. Course Readings, Online Resources, and Other Purchases

    Select readings on USF Blackboard

    F. Student Expectations/Requirements and Grading Policy

    Weekly Homework 50 Class Participation 10 Data MiningProjects 30 End of Semester Presentation 10

    G. Assignments, Exams and Tests

    Weekly Homework 50 Class Participation 10 Data MiningProjects 30 End of Semester Presentation 10

    H. Attendance Policy

    Course Attendance at First Class Meeting Policy for Graduate Students For structured courses 6000 and above the College Campus Dean will set the first day class attendance requirement Check with the College for specific information This policy is not applicable to courses in the following categories Educational Outreach Open University TV FEEDS Program Community Experiential Learning CEL Cooperative Education Training and courses that do not have regularly scheduled meeting days times such as directed reading research or study individual research thesis dissertation internship practica etc Students are responsible for dropping undesired courses in these categories by the 5th day of classes to avoid fee liability and academic penalty See USF Regulation Registration 4 0101 http usfweb2 usf edu usfgc ogc 20web currentreg htm Attendance Policy for the Observance of Religious Days by Students In accordance with Sections 1006 53 and 1001 74 10 g Florida Statutes and Board of Governors Regulation 6C 6 0115 the University of South Florida University USF has established the following policy regarding religious observances http usfweb2 usf edu usfgc gc pp acadaf gc10 045 htm In the event of an emergency it may be necessary for USF to suspend normal operations During this time USF may opt to continue delivery of instruction through methods that include but are not limited to Blackboard Elluminate Skype and email messaging and or an alternate schedule It s the responsibility of the student to monitor Blackboard site for each class for course specific communication and the main USF College and department websites emails and MoBull messages for important general information

    I. Policy on Make-up Work

    J. Program This Course Supports

    MS/MIS


  5. Course Concurrence Information

    MBA, MS in Finance, MS in Marketing (as possible elective)



- if you have questions about any of these fields, please contact chinescobb@grad.usf.edu or joe@grad.usf.edu.