Course Details

 

Course Details Language of Instruction English Level of Course Unit Bachelor's Degree Department / Program COMPUTER ENGINEERING Type of Program Formal Education Type of Course Unit Compulsory Course Delivery Method Face To Face Objectives of the Course The course provides an introduction to probability and statistics. The goal is to teach students powerful analytical and numerical tools in the areas of probability and statistics that can be used to solve real world engineering problems. Lectures will be supplemented by programming exercises and will include practical examples. Course Content Principles of counting, permutations, combinations Probability and Bayes’ theorem Random variables Expectation Central limit theorem and the law of large numbers Joint distributions, covariance and correlation Descriptive statistics Maximum likelihood estimation Bayesian inference Bayesian updating with discrete priors Bayesian updating with continuous priors Beta distributions, conjugate priors, probability intervals Frequentist inference—Null hypothesis significance testing Confidence intervals Course Methods and Techniques Grading Policy The final grades will be computed based on the general performance of the class and the distribution of grades (i.e. who deserves A and who deserves F). The grading strategy will be a combination of the standard catalogue grading and curve grading. Attendance Policy Attendance will not be taken and is not part of grading. Late Submission Policy It is the student s responsibility to follow the classes and do the quiz and exams on time. Late homework submissions will be subject to a penalty of 25% if submitted within one week after the due date and %50 if submitted after one week. Make-Up Policy There are no make-ups in homework assignments and quizzes. The student may be exempt from these assignments if a written and formal documentation is provided. Possible reasons for excused absences include serious illnesses, illness or death of a family member, university related trips and other serious circumstances. Acceptable documents for claiming an excused absence include medical doctor’s statements, petitions related to official university travels, court related documents, etc. If the student misses an exam (midterms or final) he or she can take a make-up exam upon submitting a formal document or can be exempt from the exams. Prerequisites and co-requisities ( MATH152 or MATH102 ) Course Coordinator Associate Prof.Dr. Zafer Aydın zafer.aydin@agu.edu.tr Name of Lecturers Associate Prof.Dr. ZAFER AYDIN Assistants None Work Placement(s) No Recommended or Required Reading Resources MIT Open Courseware: Introduction to Probability and Statistics https://ocw.mit.edu/courses/18-05-introduction-to-probability-and-statistics-spring-2022/ Introduction to Probability and Statistics for Engineers and Scientists, S. Ross, 6th edition, Academic Press, 2020. A First Course in Probability, 10th edition, S. Ross, Prentice Hall, 2019 Course Notes https://ocw.mit.edu/courses/18-05-introduction-to-probability-and-statistics-spring-2022/ Documents https://ocw.mit.edu/courses/18-05-introduction-to-probability-and-statistics-spring-2022/ Assignments https://ocw.mit.edu/courses/18-05-introduction-to-probability-and-statistics-spring-2022/ Exams https://ocw.mit.edu/courses/18-05-introduction-to-probability-and-statistics-spring-2022/ Course Category Mathematics and Basic Sciences %100

 
 
 
 
  
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