Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Faculty Of Computer And Information Technologies
  • Artificial Intelligence And Machine Learning Pr. (English)
  • Course Structure Diagram with Credits
  • Statistics
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications
  • ECTS Credit Load

Course Introduction Information

Code - Course Title İST2024 - Statistics
Course Type Required Courses
Language of Instruction İngilizce
Laboratory + Practice 3+0
ECTS 5.0
Course Instructor(s) DOKTOR ÖĞRETİM ÜYESİ NİHAL İNCE
Mode of Delivery This course is offered exclusively in an in-person format.
Prerequisites There are no prerequisites or co-requisites for this course.
Courses Recomended Recommended optional programme component
Required or Recommended Resources McClave, J.T. and Sincich, T. (2013). Statistics, Pearson Education.Devore, J. L. (2011). Probability and Statistics for Engineering and the Sciences (Eigth edition). Cengage learning.* Johnson, R. A. and Bhattacharyya, G.K. (2009). Statistics: principles and methods (Sixth edition). John Wiley \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\& Sons.Moore, D. S., McCabe, G. P. and Craig, B. A. (2012). Introduction to the Practice of Statistics.David R. Anderson, Dennis J. Sweeney and Thomas A. Williams, Statistics for Business and Economics, 11th Edition.Peck, R., Olsen, C. and Devore, J. L. (2015). Introduction to statistics and data analysis. Cengage Learning.Newbold, P., Carlson, W. and Thorne, B. (2013). Statistics for business and economics. Pearson.
Recommended Reading List McClave, J.T. and Sincich, T. (2013). Statistics, Pearson Education.Devore, J. L. (2011). Probability and Statistics for Engineering and the Sciences (Eigth edition). Cengage learning.Johnson, R. A. and Bhattacharyya, G.K. (2009). Statistics: principles and methods (Sixth edition). John Wiley \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\& Sons.Moore, D. S., McCabe, G. P. and Craig, B. A. (2012). Introduction to the Practice of Statistics.David R. Anderson, Dennis J. Sweeney and Thomas A. Williams, Statistics for Business and Economics, 11th Edition.Peck, R., Olsen, C. and Devore, J. L. (2015). Introduction to statistics and data analysis. Cengage Learning.Newbold, P., Carlson, W. and Thorne, B. (2013). Statistics for business and economics. Pearson.
Assessment methods and criteria 2 midterm exams, 1 final exam
Work Placement This is not suitable for this class.
Sustainability Development Goals

Content

Weeks Topics
Week - 1 EN: EN: Introduction to statistics: Basic concepts
Week - 2 EN: EN: Data organization and visualization
Week - 3 EN: EN: Descriptive statistics
Week - 4 EN: EN: EN: Shape parameters and data analytics
Week - 5 EN: EN: Probability theory and discrete probability distributions
Week - 6 EN: EN: Continuous probability distributions
Week - 7 EN: EN: Estimation theory
Week - 8 EN: EN: Introduction to hypothesis testing
Week - 9 EN: EN: Parametric hypothesis testing I
Week - 10 EN: EN:Parametric hypothesis testing II
Week - 11 EN: EN: Non-parametric tests
Week - 12 EN: EN: Korelasyon ve basit doğrusal regresyon analizi
Week - 13 EN: EN: Applied data analysis with statistical software I
Week - 14 EN: EN: Applied data analysis with statistical software II

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Demonstration
  • Problem Solving
  • Competences
  • Productive
  • Rational
  • Questoning
  • Eleştirel düşünebilme
  • Abstract analysis and synthesis
  • Problem solving
  • Applying theoretical knowledge into practice
  • To work autonomously
  • Elementary computing skills

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%) 0
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