Download Agricultural Statistics outline

The University of Jordan
Faculty: Agriculture
Department: Agricultural economics and Agribusiness
2013-2014/First semester
Course: Agricultural Statistics (605150)
----------------------------------------------------------------------------------------------------------Credit hours
Coordinator/
Lecturer
Course website
Office hours:
Day/Time
Day
Time
3
Level
Dr. Amani Alassaf
-------
Sunday
-
Office
number
E-mail
Monday
*
10:00-11:00
First year
Pre-requisite
Mathematics101
282
Office phone
22467
[email protected].
jo
Tuesday
*
9:00 -10:00
Place
Wednesday
*
10:00-11:00
132,Almagdade
Hall
Thursday
-
Course Description
The course aims at developing an understanding of the basic ideas of statistical reasoning,
i.e. what statistical analysis to be used, and how are the results of the statistical analysis
to be interpreted? The course presents statistical concepts and introduces descriptive and
inferential statistical methods of analyses and their applications in agribusiness. Students
gain hands-on experience of statistical analysis by designing and applying how to analyze
real survey data and agricultural case studies by themselves.
Learning Objectives
1- Provide students with a solid understanding of the range of statistical techniques used in
Agriculture; Special emphasis is placed on the inferences statistics
2- Learn how to design and conduct a statistical analysis in the agricultural sciences by
connecting between theory and data analysis.
3- Students are expected to understand and apply statistical concepts in a thoughtful way,
and numerical calculations, though necessary, are merely a means toward this end:
statistical analysis in agricultural science.
Intended Learning Outcomes (ILOs):
A. Knowledge and Understanding: Student is expected to
A1- Define what are statistics, population, and samples; use of proper sampling methods;
and the use descriptive and analytical statistics to analyze data based on the levels of
measurement.
1 /5
A2- Understand and be able to compute and use various descriptive measures such as the
mean, median, standard deviation and variance.
A3- Understand sufficient probability to understand the principles that underlie statistics.
A4- Understand the binomial and the normal probability distributions and how to use
them.
A5- Understand what the sampling distribution of a variable is and its relationship to the
normal distribution.
A6- Be able to estimate a population parameter with both a point estimate and an interval
estimate and will understand what this information is saying about a population.
A7- Be able to select a proper hypothesis test; to perform the test; and how to interpret
the data, i.e. to draw conclusions and derive meaningful information from the data.
A8- Understand what a simple linear regression model is and how to estimate regression
equation, and to use it for prediction.
B. Intellectual Analytical and Cognitive Skills: Student is expected to
B1- Be able to conduct exploratory data analyses through graphical and numerical
summaries.
B-2- Compute and use various descriptive measures such as the mean, median, standard
deviation and variance.
B-3 Be able to estimate a population parameter with both a point estimate and an interval
estimate and will understand what this information is saying about a population.
B4- Perform the proper hypotheses test; and how to interpret the data, and how to
estimate simple linear regression model, and to use it for prediction.
C. Subject- Specific Skills: Students is expected to
C1- Be able to conduct exploratory data analyses through graphical and numerical
summaries.
C2- Able to choose appropriate analyses from a variety of statistical methods and
implement those analyses with proficient use ; and to draw conclusions and derive
meaningful information from the data.
D. Transferable Key Skills: Students is expected to
D1- Define what are statistics, population, and samples; use of proper sampling methods;
and the use descriptive and analytical statistics to analyze data based on the levels of
measurement.
D2- Select a proper hypothesis test; to perform the test; and how to interpret the data, i.e.
to draw conclusions and derive meaningful information from the data.
D3- Be able to interpret results correctly and make inferences consistent with the study
design and communicate results effectively
2 /5
ILOs: Learning and Evaluation Methods
ILO/s
Learning Methods
Evaluation Methods
A. Knowledge
and
Understanding (A1-A8)
B. Intellectual Analytical and
Cognitive Skills (B1-B4)
C. Subject Specific Skills (C1C2)
D. Transferable Key Skills (D1D3)
Lectures and Discussions,
Homework
Lectures and Discussions,
Homework
Lectures and Discussions,
Homework
Lectures and Discussions,
Homework
Exams
Exams
Exams
Exams
Course Contents
Content
(1) INTRODUCTION:
Definitions, population, sample, variables,
observations, qualitative and quantitative
variables, continuous and discrete variables,
finite and infinite populations.
(2) DESCRIPTIVE TECHNIQUES:
Tabular and graphical description, grouped
and ungrouped data, frequency distribution,
relative frequency histogram and normal
graph-skewed.
Measures of Central Tendency: Mean,
weighted,
median,
mode,
cumulative
frequency, lower quartile, upper quartile.
Measures for Dispersion: Range, variance,
standard deviation
for (grouped and
ungrouped data) and (sample and population),
and coefficient of variation
(3) PROBABILITY THEORY:
Introduction, laws of probabilities and
mathematical expectations
(4)THE NORMAL CURVE AND NORMAL
AREA TABLE
-Relationship between frequency distribution
and probability concepts for Continuous and
discrete distributions.
Normal
distribution,
standard
normal
distribution curve, normal area table and how
to use normal area table.
(5)STATISTICAL INFERENCE :
ESTIMATION :
All possible samples with and without
replacement, regard and disregard the order of
sample space
Sampling distribution of means and sampling
distribution of proportions
Reference
Week
ILO/s
W1
Spiegel,ch1
Salvatore, ch1
Spiegel,ch2
Weiss, ch 2
A1.D1
W2-W4
W2
A1,B1,C1
Spiegel,ch3
Salvatore, ch2
W3
A2,B2,C1,
D1
Spiegel,ch4
Salvatore, ch2
W4
A2,B2,C1,
D1
Salvatore, ch3
Weiss, ch 4
W5
W5
A3,C1
W6-7
Spiegel,ch7
Salvatore, ch3
W6
A4,C1
Spiegel,ch7
Salvatore, ch3
W7
A5
W8-10
Spiegel,ch8
Salvatore, ch4
W8
A6,B3,C2,
D2
Spiegel,ch9
Salvatore, ch4
W9-10
A6,B3,C2,
D2
3 /5
(6) STATISTICAL INFERENCE :TESTING
HYPOTHESES:
Assumptions, hypothesis test statistic, attend
significance level & conclusion, large
sample, Standardized value (Z- table)
, small sample, t- table, test for mean, test for
proportion, binomial test and confidence level.
Chi- square Test ( 2), test of goodness and
independence.
Analysis of Variance: One - way
classification.
(7) REGRESSION ANALYSIS
Linear regression model for one independent
variable. -Goodness of fit, R2 coefficient
Simple Correlation
W11-14
Spiegel,ch9
Salvatore, ch5
W11
A6,A7,B3,
C2,D2,D3
Spiegel,ch11
Salvatore, ch5
Spiegel,ch12
Salvatore, ch5
Salvatore, ch2
W12
A6,A7,B3,
C2,D2,D3
A6,A7,B3,
C2,D2,D3
A6,A7,B3,
C2,D2,D3
Spiegel,ch13
Salvatore, ch6
Spiegel,ch14
Salvatore, ch6
W13
W14
W15-16
W15
W16
A8,B4,C2,
D2,D3
A8,B4
Learning Methodology
The learning methodology will be mainly based on lectures, discussions, and analyzing theoretical
exercises related to agricultural science. In this course students are expected to attend classes on time, and
fully participate in class work and discussions. Student’s attendance is crucial, as each class builds upon the
previous class session. Actual participation in class work is a very important part of the learning experience
in this course, so each student is expected to come and to be prepared to do the work, ask questions, and
fully engage with the course.
Evaluation
Evaluation
First Exam
Second Exam
Final Exam
Point %
Date
25
25
50
28/10/2013
25/11/2013
Will be determined by the
registration department
Main Reference/s:


Spiegel, M , Statistics, Schaum’s Outline Series, McGraw - Hill Book Company, New York,
USA. Arabic version 1972
Salvatore, D. “Theory and Problems of Statistics and Econometrics” , Schaum’s Outline.
Series in Economics, McGraw-Hill Book Company, New York, 1982.
References:

Weiss, Neil , 2002, Introductory Statistics, Addison-Wesley Publishing Company, Reading,
Massachusetts, USA.
4 /5
Notes:


Concerns or complaints should be expressed in the first instance to the module
lecturer; if no resolution is forthcoming, then the issue should be brought to the
attention of the module coordinator (for multiple sections) who will take the concerns
to the module representative meeting. Thereafter, problems are dealt with by the
Department Chair and if still unresolved the Dean and then ultimately the Vice
President. For final complaints, there will be a committee to review grading the final
exam.
For more details on University regulations please visit:
http://www.ju.edu.jo/rules/index.htm
5 /5