Syllabus: Elementary Statistics

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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Syllabus: Elementary StatisticsTHAI 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 1Teaching StaffSubject lecturer: PhD. Pham Thanh HieuOrganization: Faculty of Basic Science, Thai Nguyen University of Agriculture and ForestryOffice Location: In the campus of universityPhone:Mobile phone: +84 917 522 383Email: phamthanhhieu@tuaf.edu.vn or hieuphamthanh@gmail.comConsultation hours: From 2 pm to 4 pm on weekly Wednesday in the office location.Short description about the lecturerI have been working as a lecturer of Mathematics in Faculty of Basic Science, Thai NguyenUniversity 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 havefinished my PhD. study of Mathematical Analysis in 2016 and my interesting research ismethods for solving variational inequalities and fixed point problems with potential applicationsin optimization.Subject OverviewStatistics is the science of data. This involves collecting, classifying, summarizing, organizing,analysing, and interpreting numerical information. Many problems arising in real-worldsituation 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 playsimportant role in many disciplines of economy, natural and social problems. Statistics is ameaningful and useful science whose broad scope of applications to business, government, andthe physical and social sciences are almost limitless.Learning OutcomesThe 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). 2Subject StructureList of lectures Week/ Time/ Contents/Topics Instructional Sections methods Lecture(s) Week 1 Chapter 1: Introduction to statistics lecture, …/…/…. Lecture 1 1.1 The science of statistics discussion 1.2. Types of statistics applications 3.0 hours 1.1-1.5 1.3. Fundamental element of statistics 1.4. Types of data 1.5. Methods of data collection Week 2 2.1. Graphical method for describing data lecture, …/…/…. Lecture 2 2.2. Numerical measures of central tendency discussion 2.3. Numerical measures of cariability 3.0 hours 2.1-2.5 2.4. Data position 2.5. Boxplot Week 3 Discussion 1 discussion …/…/…. Lecture 3 3.0 hours Week 4 Chapter 3: Probability lecture, …/…/…. Lecture 4 3.1. The role of probability in statistics discussion 3.2. Basic concepts of probability 3.0 hours 3.1-3.5 3.3. Counting rule 3.4. Event relations 3.5. Conditional probability and the multiplication rule Week 5 Chapter 3 (continued) and Chapter 4: lecture, …/…/…. Lecture 5 Discrete probability distribution discussion 3.6 3.6. Additional rule 3.0 hours 4.1-4.2 4.1. Probability distribution 4.2. Binomial distribution Week 6 Chapter 5: Normal probability distribution lecture, …/…/…. Lecture 6 5.1. Normal distribution and the standard discussion distribution 3.0 hours 5.1-5.4 5.2. Normal distribution: Finding probabilities 5.3. Normal distribution: Finding values 5.4. Sampling distribution and the central limit theorem Week 7 Discussion 2 discussion …/…/…. Lecture 7 Review for midterm exam 3 Midterm exam 3.0 hours Week 8 Chapter 6: Confidence interval lecture, …/…/…. Lecture 8 6.1. Confidence interval for the mean (large discussion 3.0 hours sample n 30) ...