Course Name Code Semester T+U Hours Credit ECTS
Probability and Statistics IST 110 2 3 + 0 3 5
 Precondition Courses Recommended Optional Courses Course Language Turkish Course Level Bachelor's Degree Course Type Compulsory Course Coordinator Dr.Öğr.Üyesi BEYTULLAH EREN Course Lecturers Dr.Öğr.Üyesi BEYTULLAH EREN, Dr.Öğr.Üyesi MİTHAT TAKUNYACI, Course Assistants Course Category Available Basic Education in the Field Course Objective Providing students with the basics of data collection, data compilation, data summarization, data analysis, and probality applications Course Content Introduction, collection of data, entering of the data, series, graphics, mean I, II, variability and division form, Index, probality and divisions, Binom distribution, Poisson distribution, Normal distribution
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Student will be able to classify raw data, determine frequency distribution; calculate and enterpret central location measurements, means, assimetry and skewness; plot graphics, histograms Lecture, Question-Answer, Self Study, Testing, Homework,
2 Student will be able to calculate determine probabilities from (discrete/continuous) probability mass functions, Binom, Poisson and Normal Distributions functions; enterpret assimetry andd skewness of distrubition. Lecture, Question-Answer, Self Study, Testing, Homework,
3 Student will be able to know hipotez testing and applyand enterpret testing for probability disrubitons. Lecture, Question-Answer, Self Study, Testing, Homework,
Week Course Topics Preliminary Preparation
1 Example, population conceptions
2 Data collection techniques
3 Data presentation techniques (Diagrams, histograms, bar graphics, cumulative frekans graphics, distribution graphics X-Y)
4 Evaulation of Data
5 Analytical and non-analytical means, standard deviation, variance, Standard error, reliability
6 Probability density functions
7 Binominal, logaritmic, normal, poisson distributions
8 Prediction and Hypothesis tests
9 t-test, variance analysis (ANOVA)
10 Correlation and regression
11 Linear regression
12 Nonlinear regression
13 İllustration and variation of the data
14 Applications
Resources
Course Notes
Course Resources
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 Comprehend science and advanced mathematics subjects fundamental to engineering; An ability to apply knowledge of mathematics, science, and engineering to solve civil engineering problems X
2 An ability to analyze and model civil engineering systems specific problems, identify and define the appropriate requirements for their solutions. X
3 An ability to design, implement and evaluate a civil engineering systems, component, process or program that meets specified requirements.
4 Use the techniques, skills, and modern tools of engineering effectively and correctly in engineering practice X
5 An ability to gather/acquire, analyze, interpret data and make decisions to understand civil engineering problems
6 An ability to work effectively in inter- and in-disciplinary teams or individually.
7 An ability to communicate effectively in Turkish and English.
8 Recognition of the need for, and the ability to access information, to follow recent developments in science and technology and to engage in life-long learning.
9 An understanding of professional, legal, ethical and social issues and responsibilities related to computer engineering.
10 Skills in project and risk management, awareness about importance of entrepreneurship, innovation and long-term development, and recognition of international standards and methodologies.
11 An understanding about the impact of Civil  Engineering solutions in a global, environmental, societal and legal context while making decisions.
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 70
1. Kısa Sınav 30
Total 100
1. Yıl İçinin Başarıya 50
1. Final 50
Total 100