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Syllabus ( MATH 401 )


   Basic information
Course title: Mathematical Statistics
Course code: MATH 401
Lecturer: Prof. Dr. Nuri ÇELİK
ECTS credits: 6
GTU credits: 3 (3+0+0)
Year, Semester: 4, Fall
Level of course: First Cycle (Undergraduate)
Type of course: Departmental Elective
Language of instruction: English
Mode of delivery: Face to face
Pre- and co-requisites: Math 308
Professional practice: No
Purpose of the course: This course is designed to provide the student with a solid background and understanding of the basic results and methods in mathematical statistics and related subjects.
   Learning outcomes Up

Upon successful completion of this course, students will be able to:

  1. construct a solid background and demostrate the basic results and methods in mathematical statistics and related subjects.

    Contribution to Program Outcomes

    1. Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
    2. Describing, formulating, and analyzing real-life problems using mathematical and statistical techniques.

    Method of assessment

    1. Written exam
    2. Homework assignment
  2. explain the meaning of statistical models, hypotesis testing and its main principles.

    Contribution to Program Outcomes

    1. Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
    2. Describing, formulating, and analyzing real-life problems using mathematical and statistical techniques.

    Method of assessment

    1. Written exam
    2. Homework assignment
  3. Learn to do point and interval estimations.

    Contribution to Program Outcomes

    1. Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
    2. Describing, formulating, and analyzing real-life problems using mathematical and statistical techniques.
    3. Ability to work in interdisciplinary research teams effectively.
    4. Exhibiting professional and ethical responsibility.

    Method of assessment

    1. Written exam
   Contents Up
Week 1: Introduction and Motivation
Week 2: Describing Data with Graphs
Week 3: Measures of center and measures of variability
Week 4: Basic probability, Discrete Random Variables
Week 5: Continuous Random Variables
Week 6: Multivariate Probablity Distributions
Week 7: Midterm I and solutions
Week 8: Functions of Random Variables
Week 9: Sampling Distributions and the Central Limit Theorem
Week 10: Estimation
Week 11: Properties of Point Estimators and Method of Estimation
Week 12: Hypothesis Testing: One-Sample
Week 13: Midterm II and solutions
Week 14: Hypothesis Testing: Two-Samples
Week 15*: -
Week 16*: Final exam
Textbooks and materials: Wackerly, D., Mendenhall, W., & Scheaffer, R. (2007). Mathematical statistics with applications. Nelson Education.7nd ed.
Recommended readings: Mendenhall, Beaver and Beaver, Introduction to Probability and Statistics, Cengage Learning
  * Between 15th and 16th weeks is there a free week for students to prepare for final exam.
Assessment Up
Method of assessment Week number Weight (%)
Mid-terms: 7, 13 60
Other in-term studies: 0
Project: 0
Homework: 0
Quiz: 0
Final exam: 16 40
  Total weight:
(%)
   Workload Up
Activity Duration (Hours per week) Total number of weeks Total hours in term
Courses (Face-to-face teaching): 14 3
Own studies outside class: 14 5
Practice, Recitation: 0 0
Homework: 0 0
Term project: 0 0
Term project presentation: 0 0
Quiz: 0 0
Own study for mid-term exam: 10 2
Mid-term: 3 2
Personal studies for final exam: 10 1
Final exam: 3 1
    Total workload:
    Total ECTS credits:
*
  * ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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