Course Name Code Semester T+U Hours Credit ECTS
Mathematical Statistics KAL 501 0 3 + 0 3 6
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level yuksek_lisans
Course Type Optional
Course Coordinator Prof.Dr. HALİM ÖZDEMİR
Course Lecturers
Course Assistants
Course Category Field Proper Education
Course Objective Mathematical statistics is an essential part of any scientific research. Mathematical statistics is always applied to the problems which arises in the areas such as the physical, social and engineering. The aim of this course is to introduce the concepts of the statistical data analysis and give the methods of it.
Course Content Fundamental concepts and notations. Probability spaces. Probability distributions of one random variable. Probability distributions of several random variables. Mathematical expected value. Sums of independent random variables. Random sample and distribution of randam sample. Statistical estimation. Statistical hypotheses and inferences.
# Course Learning Outcomes Teaching Methods Assessment Methods
1 He/she can do sampling plan related to the research area. Lecture, Question-Answer, Discussion, Drilland Practice, Simulation, Case Study, Self Study, Problem Solving, Testing, Homework, Performance Task,
2 He/she can gather data related to the research area. Lecture, Question-Answer, Discussion, Drilland Practice, Simulation, Case Study, Self Study, Problem Solving, Testing, Homework, Performance Task,
3 He/she can analyze the data. Lecture, Question-Answer, Discussion, Drilland Practice, Simulation, Case Study, Self Study, Problem Solving, Testing, Homework, Performance Task,
4 He/she can do estimation based on the data. Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Motivations to Show, Simulation, Case Study, Self Study, Problem Solving, Testing, Homework, Performance Task,
5 He/she can do prediction and planning based on the data. Lecture, Question-Answer, Discussion, Drilland Practice, Simulation, Case Study, Self Study, Problem Solving, Testing, Homework, Performance Task,
6 His/her problem-solving ability develops. Lecture, Question-Answer, Discussion, Drilland Practice, Case Study, Self Study, Project Based Learning, Testing, Homework, Performance Task,
7 He/she can comment events. Lecture, Question-Answer, Discussion, Drilland Practice, Simulation, Case Study, Self Study, Problem Solving, Testing, Homework, Performance Task,
8 He/she can do parameter selection related to his/her research area. Lecture, Question-Answer, Discussion, Drilland Practice, Simulation, Case Study, Self Study, Problem Solving, Testing, Homework, Performance Task,
9 He/she develops his/her problem-solving ability for physical problems. Lecture, Question-Answer, Discussion, Drilland Practice, Simulation, Case Study, Self Study, Problem Solving, Testing, Homework, Performance Task,
10 He/she develops his/her making presentations ability for visual evaluation. Lecture, Question-Answer, Discussion, Drilland Practice, Simulation, Case Study, Self Study, Problem Solving, Testing, Homework, Performance Task,
11 He/she develops his/her understanding and application ability on some package program for research. Lecture, Question-Answer, Discussion, Drilland Practice, Simulation, Case Study, Problem Solving, Testing, Homework, Performance Task,
12 His/her model fitting ability for research problems develops. Lecture, Question-Answer, Discussion, Drilland Practice, Simulation, Case Study, Self Study, Problem Solving, Testing, Homework, Performance Task,
Week Course Topics Preliminary Preparation
1 Fundemental concepts and notations
2 Probability spaces
3 Distribution of one random variable
4 Distribution of several random variable
5 Mathematical expected value
6 Mathematical expected value
7 Sums of independent random variables
8 Sampling and methods of sampling
9 Sample distributions
10 Organization of data
11 Analysis of data
12 Statistical estimation
13 Statistical inferences
14 Statistical inferences
Resources
Course Notes
Course Resources 1) Paul L. MEYER, Introductory probability and statistical applications, Addison-Wesley Publishing Company, USA,1970.
2) Alexander M. MOOD, Franklin A. GRAYBILL and Duane C. BOES, Introduction to the theory of statistics, McGRAWHILL BOOK COMPANY, New York, 1974.
3) Çınlar, E., Introduction to stochastic processes, Prentice-Holl, Inc., New Jersey, 1975.
4) Robert V. HOGG and Allen T. CRAIG, Introduction to mathematical statistics, Macmillan Publishing Co. Inc., New York, 1978.
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 X
2 X
3 X
4 X
5 X
6 X
7 X
8 X
9 X
10
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 70
1. Ödev 15
2. Ödev 15
Total 100
1. Yıl İçinin Başarıya 40
1. Final 60
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Performance Task (Laboratory) 1 30 30
Final examination 1 20 20
Mid-terms 1 15 15
Total Workload 161
Total Workload / 25 (Hours) 6.44
dersAKTSKredisi 6