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 AAEC-4302 Statistical Methods in Agricultural Research
   
 

Syllabus - Summer II 2009
   
 

 Instructor:

 Dr. Olga Murova

 307 C Ag. Science Bldg.

 Department of Agricultural &

 Applied Economics
 Texas Tech University
 Lubbock, TX  79409-2132

 Phone: 806-742-2024

 Fax: 806-742-1099   
 Email: olga.murova@ttu.edu

Class info: MTWHF, 11:00-11:50 a.m., Room 308

Office hours: MTWHF, 10:00 – 11:00 a.m., or by appointment.

Text: Economic Statistics and Econometrics by Thad W. Mirer.  Prentice-Hall Inc., New Jersey, 3rd Ed., 1995.

Learning objectives:

  1. To understand the fundamental concepts and procedures of simple and multiple regressions, and econometric analysis.
  2. To learn how to build and use econometric models for applied agricultural economic analysis.
  3. To set up the basis for learning more advanced econometric techniques.

 Methods for Assessing Expected Learning Outcomes: 

  1. Students will have assigned homework, which will be collected for grading.
  2. Students will be given graded and non-graded quizzes.
  3. Exams will be used for assessment.
  4. Class poling on a particular topic or concept.

Topics:

Part I (Review of familiar topics):

  1. Introduction (Chapter 1).
  2. Economic data (Chapter 2): Examination of data sets: cross-sectional data, time-series data, and panel data.
  3. Descriptive statistics (Chapter 3): Univariate statistics, linear transformation, and bivariate statistics.
  4. Frequency distribution (Chapter 4): Discrete and continuous data variables.

 Part II (Specification and estimation of regression models): 

  1. The Theory of Simple Regression (Chapters 5 and 6): Simple, single-variable regression model: specification, estimation, interpretation, measures of fit, effects of linear transformations.
  2. Theory and Applications of the Multiple Regression (Chapter 7): The general k-variable case: specification, estimation, interpretation, measures of fit, effects of linear transformations.

Part III (Probability Distributions, inference in regression analysis, and estimation problems):

    7.   The Normal and t Distributions (Chapter 10).

    8.   Sampling Theory in Regression Analysis (Chapters 11, 12, and 13): The normal regression model, the theory of the sampling distributions, hypothesis specification, basic test of significance, test for sign, tests for specific coefficient values, P-values, confidence intervals.

    9.   F Tests and Dummy Variable Outcomes (Chapter 14).

   10.  Multicollinearity (Chapter 13), Heteroscedasticity, and Autocorrelation (Chapter 15).

Attendance:

Attendance is expected at all lectures/labs.  Attendance will be recorded.  Missing more then 3 days of classes will result in reduction of your grade by half of a letter grade.  All excused absences must be supported by official notes. 

 

Grading:                                             Points:

  1. Test 1                                      100
  2. Test 2                                      100
  3. Homework                              100 = 5 x 20
  4. Quizzes                                    50
  5. Final                                        100

Total: 450

I will announce exact dates of the tests in class at least a week prior to the test.  Dates of quizzes will not be announced in advance.

Final exam will be given on August 7 between 11a.m. - 1:30 p.m. in room 308.

 Grades: A – 90-100%, B – 80-89%, C – 70-79%, D – 60-69%, F - ≤ 59%.

 

Other Important Information:

Academic honesty: There will be no tolerance for cheating or plagiarism; University policies will be enforced in such cases.

 

Inclement Weather Policy: Class will meet unless the University is closed.

 

ADA Accommodation: Any student who because of a disability may require special arrangements in order to meet course requirements should contact the instructor as soon as possible to make any necessary arrangements.  Student should present appropriate verification from AccessTECH.  No requirement exist that accommodations be made prior to completion of this approved university procedure.

 

Religious Holy Day Observance: A student who intends to observe a religious holy day should make that intention known to the instructor prior to the absence.  A student who is absent from an assignment scheduled for that day should produce completed work within a reasonable time after the absence.

 

Classroom rules and behavior:

1. Do not talk during class meetings.  Talking is disruptive to the instructor and to your fellow classmates.

2. Do not arrive late to class and do not leave the classroom during class meetings.  Exceptions may occur for medical emergency, physiological urgency or situations where prior

    instructor approval has been granted.

3. Do not use (including viewing of) communication devices (phones, etc) during class meetings.  All electronic devices should be silenced during class meetings.

4. Do not read/view other unassigned materials (newspapers, magazines, etc) during class meetings.

5. Do not exhibit disruptive posture during class meetings, e.g. sleeping, slouching, laying, resting feet/head on furniture, etc.

6. Do not use notebook computers during class meetings unless prior instructor approval has been granted.

7. Do not bring/use food and/or tobacco products during classroom meetings.

 

  

 
 

 
     
   

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Dr. Olga Murova,  Assistant Professor,  Department of Agricultural & Applied Economics, Texas Tech University
   

Summer 2006 Page updated on  07/07/2009