Syllabus Entrance
Printer Friendly
Email Syllabus

EC 315 Quantitative Research Methods
Vinlove, Kathleen F.


Mission Statement: The mission of Park University, an entrepreneurial institution of learning, is to provide access to academic excellence, which will prepare learners to think critically, communicate effectively and engage in lifelong learning while serving a global community.

Vision Statement: Park University will be a renowned international leader in providing innovative educational opportunities for learners within the global society.

Course

EC 315 Quantitative Research Methods

Semester

FA 2006 HOB

Faculty

Vinlove, Kathleen F.

Title

Associate Professor, Economics

Degrees/Certificates

Ph.D.

Office Location

Mackay 30C

Office Hours

M 11:00 – 2:00; TR 11:30 – 12:30; F 11:00 – 12:00, or by appointment

Daytime Phone

816-584-6505

E-Mail

kathleen.vinlove@park.edu

Semester Dates

August 21 to December 15, 2006

Class Days

--T-R--

Class Time

1:00 - 2:15 PM

Prerequisites

MA 120 and CS 140

Credit Hours

3


Textbook:
Soule, Peter E. Guide to Statistical Analysis for Business and Social Science.  McGraw Hill/Primis Custom Publishing, 2004.  ISBN 0-07-312532-6        

Additional Resources:

Other Required Materials:             

1) course notebook to bring to every class period

2) scientific calculator with XY or YX key (no graphic calculators or cell phones allowed during exams)3) floppy disks or memory stick for labs

4) number-two pencils for exams and quizzes 

5) activated Pirate-mail account for receiving necessary data

McAfee Memorial Library - Online information, links, electronic databases and the Online catalog. Contact the library for further assistance via email or at 800-270-4347.
Career Counseling - The Career Development Center (CDC) provides services for all stages of career development.  The mission of the CDC is to provide the career planning tools to ensure a lifetime of career success.
Park Helpdesk - If you have forgotten your OPEN ID or Password, or need assistance with your PirateMail account, please email helpdesk@park.edu or call 800-927-3024
Resources for Current Students - A great place to look for all kinds of information http://www.park.edu/Current/.


Course Description:
This intermediate level statistics course covers the fundamentals of conducting quantitative research for the social and administrative sciences. The course is organized around a research project on quantitative analysis of data. PREREQUISITES: MA 120 and CS 140. 3:0:3

Educational Philosophy:

Because the learning process is active rather than passive, I will combine lectures with the Socratic method, and student questions are always encouraged.  The use of analytical tools and application to specific, real-world examples are emphasized.    

Learning Outcomes:
  Core Learning Outcomes

  1. Write a proposal for a research project on an original multiple regression model with four independent variables.
  2. Gather data and research articles related to the multiple regression model.
  3. Use a statistical software package to regress the original model.
  4. Write a formal research report that defines and analyzes the evaluative information provided by a statistical software package, including the adjusted R-square, F statistic, t statistics, and correlation coefficients for multicollinearity.
  5. Do hypothesis testing and determine confidence intervals using the t statistic. Also,  conduct hypothesis testing using the F and Chi-square statistics.


Core Assessment:

DESCRIPTION OF CORE ASSESSMENT FOR EC 315:



All Park University courses must include a core assessment that measures the course Learning Outcomes.  The purpose of this assessment is to determine if expectations have been met concerning mastery of learning outcomes across all instructional modalities.  For this course, the core assessment is a research project that includes a written proposal and final research paper.  This project is worth 20 percent of the student's final grade and will assess students' mastery of four core learning outcomes (Learning Outcomes 1, 2, 3, and 4 listed on this syllabus).   



Research Topic Proposal 



As preparation for the final research paper, formulate an original theory about the correlation between four measurable independent variables (causes) and one measurable dependent variable (the effect).  This proposal should include the following four items. 



1)  Purpose Statement  



In one paragraph, state the correlation and identify the primary independent variable. 



State the correlation: 



“The dependent variable _______ is determined by independent variables ________, _________, ________, and ________.  



      Identify the primary independent variable: 



 The most important independent variable in this relationship is ________ because _________.” 



2)  Definition of Variables  



For each variable, write a single definition paragraph (five paragraphs total).  They should be in this order: dependent variable, primary independent variable, and remaining three independent variables. 



In addition to defining the independent variables, you must defend why each determines the dependent variable. 



For the primary independent variable, you must also cite two research sources that discuss the variable.  The sources need not be technical documents.  List these sources on the Works Cited Page.   



3)  Data Description 



You must have at least 30 observations of cross-sectional data for each of the five variables.  Thus for the final paper, you will have a data matrix that is at least 30 rows by 5 columns. 



In one paragraph, describe the data (i.e., which government agency supplies the data, what methods are used to compile them, when they were collected, etc.) and identify the specific data sources, including table numbers.  Include the data sources on your Works Cited page.  Attach a Xerox copy of the data set to the end of the proposal.  



4) Works Cited Page 



The final page of your proposal should be a Works Cited page on which you list the two research sources for the primary independent variable in the appropriate format.  You should also list the data sources, with a separate citation for each table of data. 



Final Research Paper 

Purpose Statement and Model 



1) In the introductory paragraph, state why you have chosen to analyze the dependent variable.  Then make a general statement about the model: 



The dependent variable _______ is determined by variables ________, ________, ________, and ________. 



2) In the second paragraph, identify the primary independent variable and defend why it is important. 



The most important variable in this analysis is ________ because _________.   In this paragraph, cite and discuss the two research sources you've found that support your thesis, i.e., your model. (Definitions or citations from encyclopedias are not acceptable.) 



3) Write the general form of the model, with the primary independent variable as X1: 



The model is: 



Y =Where  



Y: brief definition of Y



X1: brief definition of X1  [etc. for each variable] 



Definition of Variables 

4) Define and defend all variables, including the dependent variable.  State your expectations for each independent variable. (one paragraph for each variable, in numerical order, i.e., X1 first, then X2, etc.)You should address the following: 



<        How is the variable defined in the data source?



<        What unit of measurement is used?



<        For the independent variables: WHY does the variable determine Y?



<        What sign do you expect for the independent variable's coefficient, positive or negative?  WHY?



Data Description 

5) In one paragraph, describe the data and identify the data sources.  



<        From which general sources and from which specific tables did you take the data? (Citing a website is not acceptable.)



<        What year or years were the data collected?



<        Are there any data limitations? 



Presentation and Interpretation of Results 

6) Write the estimated (prediction) equation: 



The results are:



 = 



7) Identify and interpret the adjusted R2 (one paragraph): 



<        Define “adjusted R2.”



<        What does the value of the adjusted R2 reveal about the model?



<        If you have a low adjusted R2, how has your choice of independent variables created this result? 



8) Identify and interpret the F test (one paragraph): 



<        Using the p-value approach, is the null hypothesis for the F test rejected or not rejected?  Why or why not?



<        Interpret the implications of your findings for the model. 



9) Identify and interpret the t tests for each of the coefficients (one separate paragraph for each variable, in numerical order): 



<        Are the signs of the coefficients as you expected?  If not, why not?



<        For each of the coefficients, interpret the numerical value.



<        Using the p-value approach, is the null hypothesis for the t test rejected or not rejected for each coefficient?  Why or why not?



<        Interpret the implications of your findings for the variable.



<        Identify the variable with the greatest significance. 



10) Analyze multicollinearity of the independent variables (one paragraph): 



<        Generate the correlation matrix.



<        Define multicollinearity.



<        Are any of the independent variables highly correlated with each other?  If so, identify the variables and explain why they are correlated.



<        State the implications of multicollinearity (if found) for your model. 



11) Other (not required): 



<        If you use any of the techniques for improving results discussed in class, discuss these at the end of the paper. 



Works Cited Page 



Use the proper format to list the works cited under two headings: 


 


12) Research:  two sources 



13) Data: a separate citation for each variable



 



 

Link to Class Rubric

Class Assessment:

Course Assessment

 

Exams:   There will be four exams: three semester exams administered during the class period and an optional comprehensive final exam.  (The optional final exam will be given only to those students who missed one of the three semester exams.)  The exam average will be based on three exams and will constitute 50 percent of the final grade.  To pass this course, students must have an exam average of D or above.

 

                 Each exam will be composed of multiple-choice and problem-solving questions based on my lectures, quizzes, handouts, in-class exercises, and homework exercises.  All exams are worth 100 points.  I will curve each exam to give you an idea of your performance in terms of letter grades.  However, final letter grades will be determined by a curve of final total averages for the class.

 

                 Students may not leave the classroom during an exam.  Cell phones must be turned off and put away during exams; students who answer cell phones during an exam will be asked to turn in the exam.  No graphic calculators are allowed during exams.  Seating for exams is assigned.

 

Make-up Exams: No make-up exams will be administered during the semester.  If a student misses a semester exam, then the optional comprehensive final exam may be taken, and this grade will replace the semester exam grade.  If a student misses a semester exam and does not take the optional final exam, then one exam grade will be zero points.

 

Late Arrivals to Exams:  Students arriving late to an exam may take the exam only if no other student has turned in the exam.  If another student has completed the exam, the late student cannot take the exam.

 

Quizzes:  Six quizzes will be given during the semester.  Each quiz is worth 20 points and is based on lectures, homework exercises, in-class exercises, and handouts.  The lowest quiz grade will be dropped and thus the final quiz grade will be based on five quizzes for a total of 100 points; this will constitute 15 percent of the final grade.  Students who do not hand in a quiz at the end of the hour (before I leave the classroom) will receive zero points for that quiz.  No make-up quizzes will be given.

 

In-class Exercises:       Five in-class exercises worth 25 points each will be given periodically during the semester, primarily during computer labs.  One in-class exercise grade will be dropped for a total of 100 points.  These points will constitute 10 percent of the final grade.

 

Homework Exercises: Homework exercises are designed to help students practice for quizzes and exams. These will be handed out periodically during the semester but will not be collected.  Instead, students may ask specific questions about the homework during class time.

 

Research Project:        A research project proposal and paper will be worth 25 percent of the final grade.  The proposal and paper are both graded on a 100-point scale; the proposal is weighted as 40 percent and the final paper as 60 percent of the final research project grade.  Both must be handed in at the beginning of the class period on the deadline date for full credit.  The following dates should be noted for the research project:

 

                                       Tuesday, October 10, beginning of class                                 proposal deadline

                                                    During class Tuesday, October 10                                                                 minus 10 points

                                                    Between Tuesday, October 10 and Friday, Oct. 13 noon                            minus 35 points

                                                    Between Friday, Oct. 13 noon and Oct. 24's class                                       minus 45 points

                                                    After October 24 (class time)                                                                            zero points

                                                    Tuesday, December 5, beginning of class                                final paper deadline

                                                    During class time, Tuesday, December 5                                                     minus 10 points

                                                    Between deadline and Wednesday, Dec. 13, 10:00 a.m.                           minus 45 points

                                                    After Wednesday, Dec. 13, 10:00 a.m.                                                            zero points

Grading:

Grading Plan:                        Final grades will be based on the following percentages:

 

Exams                                                                         50%

Quizzes                                                                      15%

Research Project                                                        25%

In-class exercises                                                       10%

 

NOTE: For students' whose grade is borderline, I will consider attendance and number of in-class exercises completed.

Late Submission of Course Materials:
10 points subtracted for being more than 10 minutes late to in-class exercises; 10-45 points subtracted for late proposal submission; 10-45 points subtracted for late research papers

Classroom Rules of Conduct:

The professor assumes that students are adults and will conduct themselves accordingly.

Course Topic/Dates/Assignments:

EC315: Course Schedule, Fall 2006

Week     Topic                                                                                                     Chapters

     1         Review: Fundamentals of Statistics                                                          1

                                      

     2         Review: Fundamentals of Statistics, continued

                Quiz #1: Thursday, August 31

 

     3         Hypothesis Testing                                                                                     2                       

               Lab #1                                                                                                        

 

     4         Continued       

               Quiz #2: Thursday, September 14                                                        

 

5                 Simple Linear Regression Analysis                                                           10, 11

First Exam: Thursday, September 21

 

     6         Simple Linear Regression Analysis, continued

 

     7         Continued       

               Quiz #3: Thursday, October 5

 

     8         Multiple Regression/The f distribution                                                        10, 4     

                Lab #2

                Research Proposal Due: Tuesday, October 10                                  

 

     9         Continued                                                                                                  

               Quiz #4: Thursday, October 26

 

10             Continued                                                                                                   15

Second Exam: Thursday, November 2

 

     11       Improving Regression Results                                                                  

               Lab #3

 

     12       Continued

               Quiz #5: Thursday, November 16

 

     13       Tests of Difference Between Two Means                                                  3           

 

     14       The Chi-square Distribution                                                                       6           

               Quiz #6: Thursday, November 30

 

15             Continued; Review

           Research Paper Due: Tuesday, December 5

Third Exam:  Thursday, December 7

 

                    Optional Final Exam:  Tuesday, December 12, 1:00 – 3:00 p.m.

Academic Honesty:
Academic integrity is the foundation of the academic community. Because each student has the primary responsibility for being academically honest, students are advised to read and understand all sections of this policy relating to standards of conduct and academic life.   Park University 2006-2007 Undergraduate Catalog Page 87-89

Plagiarism:
Plagiarism involves the use of quotations without quotation marks, the use of quotations without indication of the source, the use of another's idea without acknowledging the source, the submission of a paper, laboratory report, project, or class assignment (any portion of such) prepared by another person, or incorrect paraphrasing. Park University 2006-2007 Undergraduate Catalog Page 87

Attendance Policy:
Instructors are required to maintain attendance records and to report absences via the online attendance reporting system.

  1. The instructor may excuse absences for valid reasons, but missed work must be made up within the semester/term of enrollment.
  2. Work missed through unexcused absences must also be made up within the semester/term of enrollment, but unexcused absences may carry further penalties.
  3. In the event of two consecutive weeks of unexcused absences in a semester/term of enrollment, the student will be administratively withdrawn, resulting in a grade of "W".
  4. A "Contract for Incomplete" will not be issued to a student who has unexcused or excessive absences recorded for a course.
  5. Students receiving Military Tuition Assistance or Veterans Administration educational benefits must not exceed three unexcused absences in the semester/term of enrollment. Excessive absences will be reported to the appropriate agency and may result in a monetary penalty to the student.
  6. Report of a "F" grade (attendance or academic) resulting from excessive absence for those students who are receiving financial assistance from agencies not mentioned in item 5 above will be reported to the appropriate agency.

Park University 2006-2007 Undergraduate Catalog Page 89-90

Disability Guidelines:
Park University is committed to meeting the needs of all students that meet the criteria for special assistance. These guidelines are designed to supply directions to students concerning the information necessary to accomplish this goal. It is Park University's policy to comply fully with federal and state law, including Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities Act of 1990, regarding students with disabilities. In the case of any inconsistency between these guidelines and federal and/or state law, the provisions of the law will apply. Additional information concerning Park University's policies and procedures related to disability can be found on the Park University web page: http://www.park.edu/disability .



Rubric

CompetencyExceeds Expectation (3)Meets Expectation (2)Does Not Meet Expectation (1)No Evidence (0)
Evaluation                                                                                                                                                                                                                                                 
Outcomes
1                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Four independent variables are appropriately chosen and are measurable. Two to three independent variables are appropriately chosen and are measurable. One independent variable is appropriately chosen and is measurable. No independent variables are appropriately chosen and no variables are measurable. 
Synthesis                                                                                                                                                                                                                                                  
Outcomes
2                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Data for five variables are appropriate and documented; two research articles are cited. Data for two to four variables are appropriate and documented; two research articles are cited. Data for one variable are appropriate and documented; one research article is cited. No data are appropriate or documented; no research articles are cited. 
Analysis                                                                                                                                                                                                                                                   
Outcomes
4                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
All of the following statistics are perfectly analyzed: R2, F statistic, four t statistics, and correlation coefficients for multicollinearity Three to seven of the following statistics are perfectly analyzed: R2, F statistic, four t statistics, and correlation coefficients for multicollinearity Two to one of the following statistics are perfectly analyzed: R2, F statistic, four t statistics, and correlation coefficients for multicollinearity None of the following statistics is analyzed: R2, F statistic, four t statistics, and correlation coefficients for multicollinearity 
Application                                                                                                                                                                                                                                                
Outcomes
3                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
All statistical results are generated with no errors. All statistical results are generated with only one error. All statistical results are generated with two or more errors. Statistical results are not generated. 
Content of Communication                                                                                                                                                                                                                                   
Outcomes
4                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Works Cited page is properly formatted and complete. Works Cited page has one to two errors. Works Cited page has three or more errors. Works Cited page is not present. 
Technical Skill in Communicating                                                                                                                                                                                                                           
Outcomes
4                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
All of the following statistics are perfectly defined: R2, F statistic, t statistic, and correlation coefficients/multicollinearity Two to three of the following statistics are correctly defined: R2, F statistic, t statistic, and correlation coefficients/multicollinearity One of the following statistics is correctly defined: R2, F statistic, t statistic, and correlation coefficients/multicollinearity None of the following statistics is defined: R2, F statistic, t statistic, and correlation coefficients/multicollinearity 
First Disciplinary Competency                                                                                                                                                                                                                              
Outcomes
4                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
The p-value approach to hypothesis testing is perfectly defined and analyzed for all four t-tests. The p-value approach to hypothesis testing is defined and analyzed for two to three t-tests. The p-value approach to hypothesis testing is defined and analyzed for one t-test. The p-value approach to hypothesis testing is not defined or analyzed for any t-test. 

Copyright:

This material is protected by copyright and can not be reused without author permission.

Last Updated:8/18/2006 4:36:12 PM