Course Outline for AGSC 137
Agricultural Statistics
Spring 2019
Blackboard Access of Course Material Online (for students enrolled in the course)
INSTRUCTOR:
Dr. Walid H. Shayya 
Instructor Contact Information

GENERAL COURSE DESCRIPTION:
AGSC 137 involves the application of procedures and techniques for collecting, analyzing, and interpreting agricultural data. The course encompasses an introduction to statistical methods using examples and applications to which students can easily relate. The course also focuses on teaching students basic statistical analysis using the MS Excel spreadsheet program and other pertinent computer tools. Students enrolled in AGSC 137, which is part of the laptop curriculum, will be introduced to these important concepts through lectures and exercises that they may complete on their laptops. Emphasis will be placed on providing the student with problemsolving skills and the ability to interpret the results of basic agricultural statistical analysis. Following a brief introduction to statistics and statistical inference, students enrolled in AGSC 137 are introduced to common measures of central tendency and dispersion used in summarizing agricultural data followed by an introduction to the main concepts of probability and probability distributions and their potential applications in agricultural sciences. Additional topics to be covered include random sampling, confidence intervals, hypothesis testing, correlation analysis, and linear regression (simple and multiple).
Prerequisite: MAGN 101 or equivalent
3 credits* (3 lecture hours), spring semester* Credits do NOT count if a student successfully completes MATH 123.
EXPECTED COURSE OUTCOMES:
At the successful completion of AGSC 137, the student is expected to have developed the skill to:
Analyze and evaluate problems that involve descriptive statistics, probability distributions, random sampling, confidence intervals, hypothesis testing, correlation analysis, and linear regression as related to agricultural science.
Understand the types of problems in agriculture that can be analyzed statistically.
Utilize statistical concepts to interpret agricultural data.
Use MS Excel effectively to analyze data and solve problems.
OFFICE HOURS:
The instructor has the following designated office hours per week:
Mondays: 1:00 to 1:50 p.m.
Tuesdays: 11:00 to 11:50 a.m.
Wednesdays: 1:00 to 1:50 p.m.
Thursdays: 11:00 to 11:50 a.m.
Fridays: 1:00 to 1:50 p.m.
If necessary, students are also encouraged to make appointments to see the instructor at other times.
CONTACT HOURS AND CLASS SCHEDULE:
AGSC 137 is a threecredit hour course. It includes three contact hours per week for 14 weeks. One section of the course is offered during the 2019 Spring semester. The schedule of the offered section is as follows:
 AGSC 137  Section 1: Meets on Mondays and Wednesdays (9:30 to 10:45 a.m.) in Room 102, Marshall Hall.
TEXTBOOK(S):
Caldwell, S. 2013. Statistics Unplugged. Wadsworth, Belmont, California (ISBN: 9780840029430).
Shayya, W.H. 2014. Using MS Excel 2013 to Analyze Data: An Introductory Tutorial (online tutorial).
Shayya, W.H. 2011. Using MS Excel 2010 to Analyze Data: An Introductory Tutorial (online tutorial).
Shayya, W.H. 2008. Using MS Excel 2007 to Analyze Data: An Introductory Tutorial (online tutorial).
Shayya, W.H. 2003. Using MS Excel 2003 to Analyze Data: An Introductory Tutorial (online tutorial).
STUDENTS WITH DISABILITY:
Any student who feels s/he may need an accommodation based on the impact of a disability should contact the Disability Services (DS) office immediately to register for services and receive a Notification of Disabilities form. Once you have this form, we will meet privately, to discuss your specific needs. Although you may register for services at any time, please attempt to make arrangements within the first two weeks of the semester so all appropriate academic accommodations can be set.
CLASS POLICIES:
Attendance: First and foremost, students must always plan to be in class on time. Given the nature of the course, students are also required to attend all classes. Attendance will be taken during each class session and appropriate action will be taken when any given students has more than 3 unexcused absences during the semester. A student with a few or no class absences during the semester will receive favorable considerations during the grading process when s/he is close to receiving the next higher letter grade. No makeup examination will be given without a written medical excuse, family emergency, or prior permission from the instructor. Students are responsible for all materials covered in the class whether assigned or presented orally during the lectures.
Student Behavior: As students in a technical program are preparing for a professional career, all students are expected to conduct themselves as professionals (in both manner and dress). Good behavior in the classroom is expected from all students. Students who engage in unacceptable or disruptive behavior will be asked to leave the class.
Eating, drinking, or the consumption of any tobacco products is prohibited in the classroom situation (lecture hall, classroom, laboratory, or field). Doing so may result in the student's dismissal from that class period and will count as an unexcused absence.
Cell phones and pagers must be turned off during instruction time. Use during or disruption of class by these devices will result in the student's dismissal from that class period and an unexcused absence. Laptop computers may not be used during the lecture.
Assignments: This course will include twelve homework assignments of equal weights. At the end of the semester, the assignment with the lowest grade for each student will be dropped. Class assignments will account for 20% of the final grade. Therefore, it is important that students complete those assignments accurately, neatly, and on time. Assignments received past the due date will be devalued 5% for each day that the item is late. No class assignment of any student will be graded (for credit) once the same assignment is corrected and returned to the class. A student missing an assignment will receive a grade of zero on that assignment.
Examinations: There will be two class examinations and a comprehensive final in AGSC 137. Class examinations will cover class material, homework assignments, and assigned readings.
Honesty Policy and Discipline (Due Process): Honesty and integrity are major elements in professional behavior and are expected of each student. Any assignment (including those in electronic media) submitted by a student must be of the student's original authorship. Representation of another's work as the student’s own shall constitute plagiarism. Cheating, in any form, is an unacceptable behavior within all college courses. Students having academic problems should consult with their academic advisor or a college counselor. Instances of cheating will be dealt with in accordance to Morrisville State College policy. Standards of academic honesty and due process procedures for Morrisville State College are located in the Rules, Regulations, and Expectations section of the Student Handbook.
Safety Guidelines: Certain class assignments may require the student to be absent from the professor's immediate supervision. Whether the student is under immediate supervision or not, safe conduct and safe use of equipment shall be the ultimate rule. Failure to comply with prudent safety practice and/or willful disregard for class participants and/or equipment may be cause for immediate dismissal from that particular class session by the professor. Subsequent similar activity may be cause for dismissal from the course by the Dean.
Things to remember: The material covered in AGSC 137 will require a consistent effort from each student (understanding earlier lectures will be crucial to grasping concepts presented in subsequent lectures). Each student should plan to spend at least two hours per week for every lecture convened in class. Students are also urged to spend the time in solving problems and completing the required homework assignments on time (and independently). Solving additional problems from the text and revisiting the problems solved in the class will be very helpful. Completing assignments well before the due date will give the student a chance to ask questions should he/she encounter problems. Students also should remember to ask questions of the instructor when they face difficulties, whether inside or outside the classroom. The instructor has an opendoor policy and welcomes the opportunity to visit with students whenever needed.
GRADING/EVALUATION OF STUDENT:
Evaluation is a shared responsibility between the teacher and the student. The purpose of the evaluation is to demonstrate how well the professor has taught and the student has learned specific course materials, the principles, concepts, and terms relevant to the covered topics. Evaluation is also intended to assess the student's ability to utlize the acquired knowledge and how s/he can use this knowledge in problemsolving.
The breakdown of grading in this course will be as follows:
Class Work Ethic and Participation ==> 5% of final grade
Homework Assignments ==> 20% of final grade
First Examination (during the second lecture of the 6^{th} week) ==> 20% of final grade
Second Examination (during the two lectures of the 12^{th} week) ==> 20% of final grade
Final Examination (comprehensive) ==> 35% of final grade
The distribution of grades in this course will be based on the AF College grading scheme. The letter grades correspond to the following percentage scale: A (90100%), A (8789.9%), B+ (8386.9%), B (8082.9%), B (7779.9%), C+ (7376.9%), C (7072.9%), C (6769.9%), D+ (6366.9%), D (6062.9%), and F (<60%).
OUTLINE OF TOPICS:
Lecture 
Date 
Lecture Topic* 
Textbook/Online Resources  Homework Assignment 
1 (1)  Jan. 21   Introduction to AGSC137  
2 (1)  Jan. 23 

Introduction to agricultural statistics  Variables and summation 
Chapter 1  #1, Problem Set on Summations 
3 (2)  Jan. 28   Different forms of presenting data  Chapter 2  
4 (2)  Jan. 30 
 Measuring
central tendency of ungrouped data  Measures of dispersion of ungrouped data 
Chapter 2  #2, Problem Set on Summarizing Data 
5 (3)  Feb. 4 
 Data
properties of importance  Review of descriptive statistics for ungrouped data 
Chapter 2  
6 (3)  Feb. 6   Introduction to MS Excel  Handout  #3, Excel Online Introductory Tutorial 
7 (4)  Feb. 11 
 Handson
exercise on descriptive statistics for an ungrouped data set using MS
Excel  Introduction of an exercise on descriptive statistics for a second ungrouped data set 
OnLine Handout on Common Excel Functions  
8 (4)  Feb. 13   Handson exercise on summarizing the second ungrouped data set using MS Excel  Handouts  #4, Problem Set on Summarizing Data Using MS Excel 
9 (5)  Feb. 18   Measuring central tendency of grouped data using MS Excel  Handouts  
10 (5)  Feb. 20   Measures of dispersion of grouped data using MS Excel  Handouts  #5, Problem Set on Summarizing Grouped Data Using MS Excel 
11 (6)  Feb. 25 
 Finalize
discussion on summarizing data  First exam study guide 
Handouts 

12 (6)  Feb. 27 
Progress Examination 1 

13 (7)  March 4 
 First exam
review  Data sets and set operations 
Handouts 

14 (7)  March 6 

Probability  Rules of probability 
Sample Problems 
#6, Problem Set on Probability 
Week 8  Spring Break (No classes)  
15 (9)  March 18   Probability distributions 
Chapters 3
and 4 Sample Problems 

16 (9)  March 20   Probability distribution functions in MS Excel  Handouts  #7, Problem Set on Probability Distributions 
17 (10)  March 25 
 Sampling
and sampling distributions  The Central Limit Theorem 
Chapter 5  #8, Problem Set on Sampling Distributions 
18 (10)  March 27   Confidence interval for the mean  Chapter 6  #9, Problem Set on Confidence Interval 
19 (11)  April 1 
 Confidence
intervals for proportions  Confidence intervals problems 
Chapter 6  
20 (11)  April 3 
 Hypothesis
testing  The case of null hypothesis 
Chapter 7  #10, Problem Set on Hypothesis Testing of Single Mean 
21 (12)  April 8 
 Single
sample hypothesis testing  Second exam study guide 
Chapter 7  
22 (12)  April 10 
Progress Examination 2 

23 (13)  April 15   Hypothesis testing of two sample means  Chapter 8  
24 (13)  April 17 
 Problems
on Hypothesis Testing of two samples  Analysis of variance and beyond 
Chapter 8 Chapters 911 
#11, Problem Set on Hypothesis Testing of Two Sample Means 
25 (14)  April 22 

Correlation analysis  Simple linear regression 
Chapter 12  
26 (14)  April 24   Using MS Excel to solve correlation and linear regression problems  Online Handout on Correlation and Regression Analysis Using Excel  
27 (15)  April 29 
 Multiple
linear regression  Using MS Excel to solve multiple linear regression problems 
Handouts  #12, Problem Set on Correlation Analysis and Linear Regression 
28 (15)  May 1 
 Finalize
discussion of linear regression  Final exam study guide 
Handouts  
(16)  May ? 
Final
Examination
(comprehensive)  To Be Scheduled During the Finals Week 
*The topics
listed in the table above are tentative and may be subject to change during the
semester.