Consultation hours: From 2 pm to 4 pm on weekly Wednesday in the office location.
Short description about the lecturer
I have been working as a lecturer of Mathematics in Faculty of Basic Science, Thai Nguyen
University of Agriculture and Forestry (TUAF) since 2006. I teach two courses in Vietnamese,
Short Calculus and Statistics, for the first year students of TUAF and one course in English,
Elementary Statistics, for the second year students of advanced education program in s. I have
finished my PhD. study of Mathematical Analysis in 2016 and my interesting research is
methods for solving variational inequalities and fixed point problems with potential applications
in optimization.

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THAI NGUYEN UNIVERSITY OF AGRICULTURE AND FORESTRY
INTERNATIONAL TRAINING AND DEVELOPMENT CENTER
ADVANCED EDUCATION PROGRAM
STA13
Elementary Statistics
Syllabus
Semester 2, AY 2
Picture best relevant to the subject
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Teaching Staff
Subject lecturer: PhD. Pham Thanh Hieu
Organization: Faculty of Basic Science, Thai Nguyen University of Agriculture and Forestry
Office Location: In the campus of university
Phone:
Mobile phone: +84 917 522 383
Email: phamthanhhieu@tuaf.edu.vn or hieuphamthanh@gmail.com
Consultation hours: From 2 pm to 4 pm on weekly Wednesday in the office location.
Short description about the lecturer
I have been working as a lecturer of Mathematics in Faculty of Basic Science, Thai Nguyen
University of Agriculture and Forestry (TUAF) since 2006. I teach two courses in Vietnamese,
Short Calculus and Statistics, for the first year students of TUAF and one course in English,
Elementary Statistics, for the second year students of advanced education program in s. I have
finished my PhD. study of Mathematical Analysis in 2016 and my interesting research is
methods for solving variational inequalities and fixed point problems with potential applications
in optimization.
Subject Overview
Statistics is the science of data. This involves collecting, classifying, summarizing, organizing,
analysing, and interpreting numerical information. Many problems arising in real-world
situation are closely related to statistics which we call statistical problems.
For example:
know if a new drug is superior (better) to already
existing drugs, or possible side effects.
opportunities?
So we can see that statistics is the science originated from the real-world problems and it plays
important role in many disciplines of economy, natural and social problems. Statistics is a
meaningful and useful science whose broad scope of applications to business, government, and
the physical and social sciences are almost limitless.
Learning Outcomes
The object (for students) in this course is
To learn how to interpret statistical summaries appearing in journals, newspaper reports,
internet, television, etc..
To learn about the concepts of probability and probabilistic reasoning.
To understand variability and analyze sampling distribution.
To learn how to interpret and analyze data arising in your own work (course work or
research).
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Subject Structure
List of lectures
Week/
Lecture(s)
Time/
Sections
Contents/Topics Instructional
methods
Week 1
Lecture 1
3.0 hours
//.
1.1-1.5
Chapter 1: Introduction to statistics
1.1 The science of statistics
1.2. Types of statistics applications
1.3. Fundamental element of statistics
1.4. Types of data
1.5. Methods of data collection
lecture,
discussion
Week 2
Lecture 2
3.0 hours
//.
2.1-2.5
2.1. Graphical method for describing data
2.2. Numerical measures of central tendency
2.3. Numerical measures of cariability
2.4. Data position
2.5. Boxplot
lecture,
discussion
Week 3
Lecture 3
3.0 hours
//.
Discussion 1 discussion
Week 4
Lecture 4
3.0 hours
//.
3.1-3.5
Chapter 3: Probability
3.1. The role of probability in statistics
3.2. Basic concepts of probability
3.3. Counting rule
3.4. Event relations
3.5. Conditional probability and the
multiplication rule
lecture,
discussion
Week 5
Lecture 5
3.0 hours
//.
3.6
4.1-4.2
Chapter 3 (continued) and Chapter 4:
Discrete probability distribution
3.6. Additional rule
4.1. Probability distribution
4.2. Binomial distribution
lecture,
discussion
Week 6
Lecture 6
3.0 hours
//.
5.1-5.4
Chapter 5: Normal probability distribution
5.1. Normal distribution and the standard
distribution
5.2. Normal distribution: Finding
probabilities
5.3. Normal distribution: Finding values
5.4. Sampling distribution and the central
limit theorem
lecture,
discussion
Week 7
Lecture 7
//.
Discussion 2
Review for midterm exam
discussion
4
3.0 hours
Midterm exam
Week 8
Lecture 8
3.0 hours
//.
6.1-6.3
Chapter 6: Confidence interval
6.1. Confidence interval for the mean (large
sample n 30)
6.2. Confidence interval for the mean (small
sample n 30)
6.3. Confidence interval for the population
proportion
lecture,
discussion
Week 9
Lecture 9
3.0 hours
//.
Discussion 3 discussion
Week 10
Lecture 10
3.0 hours
//.
7.1-7.4
Chapter 7: Hypothesis Testing for One
Sample
7.1. Introduction to hypothesis testing
7.2. Hypothesis testing for the mean (large
sample n>30)
7.3. Hypothesis testing for the mean (small
sample n<30)
7.4. Hypothesis testing for proportions
lecture,
discussion
Week 11
Lecture 11
3.0 hours
//.
Discussion 4
Review for the midterm exam 2
Midterm exam 2
discussion
Week 12
Lecture 12
3.0 hours
//.
Review all for the final exam
The sample final exam
discussion
21 hours teaching and giving the sample
midterm exams
12 hours discussing and taking the
midterm exams
3 hours for reviewing and taking the
sample final example
=36 hours
Time for Final Exam is followed the TUAF exam timetable
Reading materials:
1. Elementary statistics, Robert Johnson, Patricia Kuby, THOMSON, 2004
2. Introduction to Probability and Statistics , 13rd edition, W. Mendenhall, R.J. Beaver, and
B.M. Beaver, Books/Cole, Cengage Learning, 2009.
3. Applied Statistics, M. A. Shayib, bookboon.com, 2013.
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Attendance/ Participation Requirements
Lecture Attendance Requirement:
Attendance at all lectures is expected. If, for whatever reason, you cannot attend the lecture,
please let the lecturer know in advance. You are required to attend a minimum of 75% of
lectures.
Assessment
The assessment for this course will be in the form of homework, one midterm exam and one
final exam. Midterm will take place in class on the 7
th
week of the course, and the final
examination will take place in class following the exam timetable of TUAF.
Your overall grade will be based on: Homework/Attendance/Attitude: 20%; Midterm - 30%;
Final - 50%
The use of calculators, books or notes will not be allowed in the examinations.
Assessment for this subject consists of :
Assessment type Percentage Due Date
Midterm exam 30% The 7
th
week
Final exam 50% After the 12
th
week.
Assessment Criteria: Students should obtain at least 40 points in total 100 points for each
exam.
Grading system
Grade
in letter
1-4
scale
1-10
scale
Description
A 4 8.5 – 10 Excellent analysis, comprehensive research,
sophisticated theoretical or methodological
understanding, impeccable presentation;
Work that meets all the key assessment criteria and
excels in most;
Work that meets these criteria and is also in some way
original, exciting or challenging could be awarded
marks in the high 8 or above.
Marks of 9 and above may be awarded to the best
student work in the range.
B 3 7 – 8.49 Good work that is solidly researched, shows a good
understanding of key ideas, demonstrates some use of
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critical analysis along with good presentation and
documentation;
Work that meets most of the key assessment criteria
and performs well in some;
Work that shows some room for improvement.
C 2 5.5 –
6.99
Completion of key tasks at a satisfactory level, with
demonstrated understanding of key ideas and some
analytical skills, and satisfactory presentation,
research and documentation;
Work that meets most of the key assessment criteria;
Work that shows room for improvement in several
areas.
D 1 4 – 5.49 Completion of key tasks at an adequate level of
performance in argumentation, documentation and
expression;
Work that meets a limited number of the key
assessment criteria;
Work that shows substantial room for improvement in
many areas.
F 0 1-3.99 Work that fails to meet the basic assessment criteria;
Work that contravenes the policies and regulations set
out for the assessment exercise;
Where a student fails a subject, all failed components
of assessment are double marked.
Extension Policy and Late Submission of Work
Late work is not accepted. If, however, you find that it is absolutely impossible for you to make
a given deadline due to illness or other unforeseen circumstances, you may negotiate a short-
term extension of up to 5 working days. But please note: Extensions are not granted after due
dates have passed.
Penalty for Submission of Late Assessment
Assessment submitted late without an approved extension will be penalised at 2% per working
day. In-class tasks missed without approval will not be marked and in-semester tests and exams
that are submitted late without an approved extension will not be accepted.
Plagiarism
Plagiarism is academic misconduct, and is taken very seriously by the Program and
University. Any acts of suspected plagiarism detected by assessors will be followed up, and any
students involved will be required to respond via the Program and/or University procedures for
handling suspected plagiarism. If you have questions about how to appropriately acknowledge
your sources, please let the lecturer know.