Course Name Code Semester T+U Hours Credit ECTS
Probability and Statistics IST 108 2 3 + 0 3 4
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Compulsory
Course Coordinator Dr.Öğr.Üyesi SEÇKİN ARI
Course Lecturers Dr.Öğr.Üyesi ABDULLAH SEVİN, Dr.Öğr.Üyesi SEÇKİN ARI, Dr.Öğr.Üyesi SÜMEYYE KAYNAK,
Course Assistants
Course Category
Course Objective Aim of this course is to obtain strong mathematical background, collect data gained with tests and observation, and arrange and evaluate them, intensify connections with mathematics, engineering and social sciences.
Course Content Definition of statistic, kind of statistic and application areas. Variables,graps and frecuency Dispertion. Data collection and evaluation. Averages. Variability measures. Probability, conditional probability. Multiplication rule. Dependent and independent events. Bayes rule. Random variables. Probability function. Dispertion function. Expected value. Variance and standart deviation. Continual random variables. Interrupted Dispertion. Continual distribution. Hypothesis tests.
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Student defines concepts related to probability and statistics, Lecture, Question-Answer, Drilland Practice, Testing, Homework,
2 Mathematically models complex probability problems expressed verbally, Lecture, Question-Answer, Drilland Practice, Testing, Homework,
3 Calculates expectations and variances of the results of repeated problems, Lecture, Question-Answer, Drilland Practice, Testing, Homework,
4 Provides solutions to daily and Computer Engineering problems with proper probability distributions, Lecture, Question-Answer, Drilland Practice, Testing, Homework,
5 Solves probability problems with computer aid, Lecture, Question-Answer, Drilland Practice, Testing, Homework,
6 Gains ability to solve a problem with theoretical and statistical techniques, Lecture, Question-Answer, Drilland Practice, Testing, Homework,
7 Statistically analyzes collected data Lecture, Question-Answer, Drilland Practice, Testing, Homework,
8 Forms and solves hypothesis tests Lecture, Question-Answer, Drilland Practice, Testing, Homework,
Week Course Topics Preliminary Preparation
1 Sets, cartesian multiplication and their applications.
2 Basic concepts
3 Statistical data, data collection, table and graphs
4 Position measures
5 Dispertion measures
6 Probability and their Dispertion.
7 Continual probability Dispertion
8 Interrupted probability Dispertion
9 Interrupted probability Dispertion and applications
10 Hypothesis tests
11 Hypothesis tests
12 Regression and correlation analysis
13 Variance analysis technic
14 Applications
Resources
Course Notes Assist.Prof.Dr. Ferhat DİKBIYIK Lecture Notes
Course Resources Introduction to Probability and Statistics for Engineers and Scientists, 2nd Ed., S. M. Ross, Elseiver, 2000.
A First Course in Probability, 6th Ed., S. M. Ross, Prentice-Hall, 2002
Probability, Random Variables and Stochastic Processes, 4th Ed., A. Papoulis and S. U. Pillai, McGraw-Hill, 2002.
Probability Models for Computer Science, 1st Ed., S. M. Ross, Harcourt, 2002.
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 To have sufficient foundations on engineering subjects such as science and discrete mathematics, probability/statistics; an ability to use theoretical and applied knowledge of these subjects together for engineering solutions, X
2 An ability to determine, describe, formulate and solve engineering problems; for this purpose, an ability to select and apply proper analytic and modeling methods,al background in describing, formulating, modeling and analyzing the engineering problem, with a consideration for appropriate analytical solutions in all necessary situations X
3 An ability to select and use modern techniques and tools for engineering applications; an ability to use information technologies efficiently,
4 An ability to analyze a system, a component or a process and design a system under real limits to meet desired needs; in this direction, an ability to apply modern design methods,
5 An ability to design, conduct experiment, collect data, analyze and comment on the results and consciousness of becoming a volunteer on research, X
6 Understanding, awareness of administration, control, development and security/reliability issues about information technologies,
7 An ability to work efficiently in multidisciplinary teams, self confidence to take responsibility, X
8 An ability to present himself/herself or a problem with oral/written techniques and have efficient communication skills; know at least one extra language,
9 An awareness about importance of lifelong learning; an ability to update his/her knowledge continuously by means of following advances in science and technology,
10 Understanding, practicing of professional and ethical responsibilities, an ability to disseminate this responsibility on society, X
11 An understanding of project management, workplace applications, health issues of laborers, environment and job safety; an awareness about legal consequences of engineering applications,
12 An understanding universal and local effects of engineering solutions; awareness of entrepreneurial and innovation and to have knowledge about contemporary problems.
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 70
1. Ödev 10
2. Ödev 10
3. Ödev 10
Total 100
1. Yıl İçinin Başarıya 60
1. Final 40
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 2 32
Mid-terms 1 4 4
Assignment 3 4 12
Final examination 1 6 6
Total Workload 102
Total Workload / 25 (Hours) 4.08
dersAKTSKredisi 4