ISYE 4031 Syllabus
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ISYE 4031 A: Regression and Forecasting Summer 2014 Instructor : Justin Lars Kirkby Time/Location : MWF 4:00-5:10 pm, Instructional Center 111 Office : ISYE Studio, 1 st Floor of Main Building Office Hours : Monday 5:10-6:30 or by appointment Email : [email protected] Phone : (757) 613 9481 Grader/TA : Laura Tschirn, [email protected] Textbook: Forecasting, Time Series, and Regression, 4 th Edition, by Bowerman, O’Connel, and Koehler, Duxbury Applied Series Software: R, download from http://www.r-project.org/ Objective: Learn about simple and multiple linear regression, as well as time series and forecasting techniques. Develop the skills necessary to critically interpret and conduct statistical analyses. Gain familiarity with statistical software required for analyzing real world data. Topics Covered: simple regression, multiple regression, hypothesis testing, model building and residual analysis, basic time series analysis, exponential smoothing, seasonality, Box-Jenkins Methodology, advanced time series topics as time permits Grading: Exam 1 (Friday June 13 th ) : 25% Exam 2 (Friday July 11 th ) : 25% Final Exam : 30% Homework : 20% GT Honor Code: Make sure that you are fully aware of the Georgia Tech honor code, which is available for your review at www.honor.gatech.edu. You will be allowed to discuss homework assignments with other students, but the work you turn in must be your own.
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Syllabus ISYE 4031 ga tech
Transcript of ISYE 4031 Syllabus
ISYE 4031 A: Regression and Forecasting
Summer 2014
Instructor : Justin Lars Kirkby
Time/Location : MWF 4:00-5:10 pm, Instructional Center 111
Office : ISYE Studio, 1st Floor of Main Building
Office Hours : Monday 5:10-6:30 or by appointment
Email : [email protected]
Phone : (757) 613 9481
Grader/TA : Laura Tschirn, [email protected]
Textbook: Forecasting, Time Series, and Regression, 4th Edition, by Bowerman, O’Connel, and Koehler,
Duxbury Applied Series
Software: R, download from http://www.r-project.org/
Objective: Learn about simple and multiple linear regression, as well as time series and forecasting
techniques. Develop the skills necessary to critically interpret and conduct statistical analyses. Gain
familiarity with statistical software required for analyzing real world data.
Topics Covered: simple regression, multiple regression, hypothesis testing, model building and residual
analysis, basic time series analysis, exponential smoothing, seasonality, Box-Jenkins Methodology,
advanced time series topics as time permits
Grading:
Exam 1 (Friday June 13th) : 25%
Exam 2 (Friday July 11th) : 25%
Final Exam : 30%
Homework : 20%
GT Honor Code: Make sure that you are fully aware of the Georgia Tech honor code, which is available
for your review at www.honor.gatech.edu. You will be allowed to discuss homework assignments with
other students, but the work you turn in must be your own.
