Course Syllabus - Introduction to Decision Making | DSCI 5180D, Lecture notes of Humanities

Download Course Syllabus - Introduction to Decision Making | DSCI 5180D and more Lecture notes Humanities in PDF only on Docsity! Syllabus: DSCI 5180 Introduction to Decision Making - DSCI 5180 Sections 002,026 (Spring 2011) Jayakumar Section Information: DSCI 5180 Sections 002,026 (Spring 2011) Jayakumar Course Name DSCI 5180 Introduction to Decision Making Course Information Introduction DSCI 5180.001. INET: NO scheduled class meeting (Ends with the on-line final exam. closing at 11:45pm, Thursday, May 12th) INSTRUCTOR: Dr. Jay Jayakumar. OFFICE: 302E BUSINESS Bldg. EMAIL: jaykumar@unt.edu OFFICE PHONE: 940-565-4146 or ITDS Dept. @ 940-565-3110 OFFICE HOURS: Tuesdays, Thursdays 12:30 to 2pm: to chat and for physical meetings by appointments (also reachable through vista-mail and via. the module discussion boards). TEXTBOOKS: (Required) TEXT: Applied Regression Analysis - A Second Course in Business and Economic Statistics, 2005, 4th Ed. Prof. Terry E. Dielman, Duxbury. with the data and software disc. (Optional) Student Solutions Manual for Applied Regression Analysis, 4th Ed. Prof. Terry E. Dielman. (Microsoft Excel with the Macros furnished with the Text prescribed above will be used for all the assignments/ illustrations. Use of other statistical software such as Minitab, SPSS, or SAS is completely optional; and their use is not covered for the general class.) GRADING: 11 timed, on-line quizzes (@20 pts each) .. 220 pts Final Examination (in 2 parts) ................... 80 pts Total .......... 300 pts (With the usual +90% for A, +80% for B, etc. for the letter grades.) Syllabus http://www.cob.unt.edu/itds/courses/dsci5180/Syllabus.htm 1 of 14 12/15/2011 10:35 PM Requirements The completion dates for the different assignments are given elsewhere in this syllabus, and in the module folios. But they may be done anytime prior to taking the assessment quizzes. The assessment quizzes, based on module work (assignments) are scheduled for thursdays: Feb. 3, 10, 24; Mar. 3, 10, 24, 31; Apr. 7, 14, 21, and 28th. These quizzes are of 30 min. (max.) duration, and may be taken anytime between 5:15 pm and 11:45 pm. This arrangement allows you maximum flexibility with respect to completing the work. The timely completion of the quizzes is of the essence. Allow yourself sufficient quiz-time by starting early (before 11:15 pm, to avail all 30 mins.) The final exam. will have two parts: viz., a written paper (or project, for 60 points) and a comprehensive summary quiz (similar to the assessment quizzes, for 20 points)...more on this later.... IMPORTANT All module-quizzes may be accessed through the menu item 'ASSESSMENTS' from the course homepage (on the side-bar). A mock-quiz has been setup only to familiarize you with the process of quiz-taking. Please utilize, by taking it in advance of the assessment quiz #1. Again, the mock-quiz needs no reading of statistics, and does not count toward the course. So, please attempt it, just to to be at ease. All quizzes will follow similar format. When viewing the list of assessments for taking the Mock-quiz, please reset the number of items to be shown on the page to 15. This will make all quizzes show up on the same page, as and when several of them get enabled, through the course. Each 30 min. quiz is to be done any time in the extended 5:15 - 11:45 time-window, on the dates posted here. Each quiz should be taken in a continuous time window, not exceeding 30 minutes (the format allows NO breaks). Please plan accordingly... also, please ignore the dates posted in the printable versions of the assignments. Policies Introduction There are two major objectives for this course. The first is to develop an understanding of regression analysis and its assumptions and approaches. The second is to strengthen your ability to make business decisions through its use. The course will achieve its objectives by using an illustration-based quiz approach, with data from multiple business disciplines. Multiple regression/correlation as well as the other statistical methodologies contained in this course are highly general and are widely used. Accordingly, a third objective of this course is to develop competency in applying the subject methodologies to real-life problems in their own business disciplines, making them better communicators in their business world. It is assumed that students taking this course have already had an introductory statistics course. However, a fair review of elementary concepts and terminology is included in the course, to refresh your memory. (The review is not a substitute for such a first course.) Finally being an applied course, DSCI 5180 does not impose high degree of mathematical rigor, but instead aims at imparting a deeper functional understanding of Regression. Syllabus http://www.cob.unt.edu/itds/courses/dsci5180/Syllabus.htm 2 of 14 12/15/2011 10:35 PM Practice using Excel's Descriptive Statistics (Text: pp. 54-57) to see similar results generated using Excel. Use Module 1 powerpoint slides as a review tool Complete Assignment #1 and verify you have the output posted in the solutions file. Take Assessment Quiz 1 based on this module between 5:45pm and 11:45pm, Feb. 3. ** PLEASE NOTE: The "Readings" list format of reference used through this syllabus is straight-forward. For example, "Ch.2 2.1 (pp. 5-7)" above refers to section #1 of Chapter #2 from the Text, pages 5 through 7. Similarly, for example, the end of section exercise 2.1 is the problem so listed under chapter 2, in the text (pp.12); 2.9 is on pp. 23 etc. The first module's illustration uses problem 2.31 (pp.39), and data from 2.26 (pp.31), as stated therein. Module 2 Review of Basic Statistics II (Contd. from Module 1) - Completed by Feb. 10 Objectives Review of back ground material (from the first course) Part II Topics Independent (Vs) Dependent Samples Point and Interval Estimates for Differences Hypothesis Tests for Differences Readings : Text - Ch.2 2.8 (pp. 40-43) Ch.2 2.9 (pp. 44-47) Assignments End of section/ chapter exercises: 2.35, 37, and 39 Practice using Excel's Descriptive Statistics to reproduce the results generated in the Text by SAS/ Minitab Use Module 2 powerpoint slides as a review tool Complete Assignment #2, verify its correctness, and take Assessment Quiz 2 based on this module, between 5:15pm and 11:45pm, Feb. 10. Syllabus http://www.cob.unt.edu/itds/courses/dsci5180/Syllabus.htm 5 of 14 12/15/2011 10:35 PM Module 3 Simple Linear Regression I - Completed by Feb 24 Objectives Introduce the concept of Simple Linear Regression (SLR) To Fit a SLR Model using data on two related variables Topics The Probabilistic Conceptual Model The available Deterministic Model Fitting the Model: The Method of Least Squares Inferences based on Estimated Slope and Intercept Readings : Text - Ch.3 3.1 (pp. 63-69) Ch.3 3.2 (pp. 70-73) Ch.3 3.3 (pp. 74-90) Assignments End of section/ chapter exercises: 3.1, and 7 Practice using Excel's Regression to reproduce similar results as those generated in the Text by SAS/ Minitab Use Module 3 powerpoint slides as a review tool Complete Assignment #3, verify its correctness, and take Assessment Quiz 3 based on this module between 5:15pm and 11:45pm, Feb. 24. Module 4 Simple Linear Regression II - Completed by Mar. 3 Objectives Deducing the existence of the (SLR) relation and using it in the prediction of future values Topics Syllabus http://www.cob.unt.edu/itds/courses/dsci5180/Syllabus.htm 6 of 14 12/15/2011 10:35 PM Assessing the Fit/ Utility of the Model - ANOVA and The Coefficient of Determination Using the Model for Estimation and Prediction Regressions on Time Causal X?- or is it only co-related X ? Readings : Text - Ch.3 3.4 (pp. 93-102) Ch.3 3.5 (pp. 103-110) Ch.3 3.6 (pp. 11-115) Ch.3 3.7 (pp. 116) Assignments End of section/ chapter exercises: 3.9, 17, and 19 Practice using Excel's Regression to reproduce similar results as those generated in the Text by SAS/ Minitab Use Module 4 powerpoint slides as a review tool Complete Assignment #4, verify its correctness, and take Assessment Quiz 4 based on this module between 5:45pm and 11:45pm, Mar. 3. Learning Integration Module Integration of SLR models in a Business Application ... Mar. 10 Illustrate practical uses of SLR models Students will use "real" data to determine the Beta's (risk) that go with selected securities, and use them in coming up with a portfolio that has a set target Beta (risk). Topics: The section uses optimization in Excel. No new topics in statistics are covered in this module. Obtain the Beta's and the target mix of securities and take this module quiz between 5:15pm and 11:45 pm, Mar. 10. Syllabus http://www.cob.unt.edu/itds/courses/dsci5180/Syllabus.htm 7 of 14 12/15/2011 10:35 PM Randomness Normality (only visual verfication of the straight line fit) Influence (outliers?) Corelation (the Durbin-Watson Statistic) Readings : Text - Ch.5 5.1 (pp. 179) Ch.5 5.2 (pp.180-182) Ch.6 6.1 (pp.205) Ch.6 6.2 (pp. 206) Ch.6 6.3 (pp. 207-209) Ch.6 6.6 (pp. 230-233) Ch.6 6.7 (pp. 239-145) Ch.6 6.8 (pp. 254-259) Assignments End of section/ chapter exercises: 6.5 and 9 Practice using Excel's Regression with SMARTReg macros of the Text to reproduce similar results as those generated in the Text (by Excel,SAS/ Minitab) Use Module 7 powerpoint slides as a review tool Complete Assignment #7, verify its correctness, and take Assessment Quiz 7 based on this module between 5:15pm and 11:45pm, April 7. Module 8 Dummy Variables and Interactions - Completed on Apr. 14 Objectives Demonstrate the use of dummy variables to categorize observations, and to run MLR Models using these and / or their interactions Syllabus http://www.cob.unt.edu/itds/courses/dsci5180/Syllabus.htm 10 of 14 12/15/2011 10:35 PM Topics Indicator Variables Creating and using interaction variables Readings : Text - Ch.7 7.1 (pp. 273-284) Ch.7 7.2 (pp. 287-288) Ch.7 7.3 (pp. 291-193) Assignments End of section/ chapter exercises: 7.1, 3, and 5 Practice using Excel's Regression with SMARTReg macros of the Text to reproduce similar results as those generated in the Text (by Excel,SAS/ Minitab) Use Module 8 powerpoint slides as a review tool Complete Assignment #8, verify its correctness, and take Assessment Quiz 8 based on this module between 5:15pm and 11:45pm, April 14. Module 9 Variable Screening : The Stepwise Procedures - Completed by Apr. 21 Objectives To introduce methods designed to automate the selection of important independent variables Topics Forward Selection Backward Elimination Stepwise (their combination) Assessing the Models Readings : Text - Syllabus http://www.cob.unt.edu/itds/courses/dsci5180/Syllabus.htm 11 of 14 12/15/2011 10:35 PM Ch.8 8.1 (pp. 311 and 312) Ch.8 8.3 and 4 (pp.318-328) Assignments End of section/ chapter exercises: 8.1 and 3 Practice using Excel's Regression with SMARTReg macros of the Text to reproduce similar results as those generated in the Text (by Excel,SAS/ Minitab) Use Module 9 powerpoint slides as a review tool Complete Assignment #9, verify its correctness, and take Assessment Quiz 9 based on this module between 5:15pm and 11:45pm, April 21. Module 10 Comparing Multiple Population means - ANOVA ... Completed by Apr. 28 Objectives Introduction to 1- and 2- way ANOVA Topics One way ANOVA Randomized block design Two-way ANOVA Readings : Text - Ch.9 9.1 (pp.335-343) Ch.9 9.2 (pp.347-348) Ch.9 9.3 (pp. 355-363) Assignments End of section/ chapter exercises: 9.1, 2, and 9 Practice using Excel's ANOVAs to reproduce similar results as those generated in the Text (by SAS/ Minitab) Syllabus http://www.cob.unt.edu/itds/courses/dsci5180/Syllabus.htm 12 of 14 12/15/2011 10:35 PM