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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS CME 2205 PROBABILITY AND STATISTICS COMPULSORY 2 2 0 4

Offered By

Computer Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR IDIL YAVUZ

Offered to

Computer Engineering

Course Objective

To make students to learn fundamental concepts of probability and statistics, to describe data sets by graphical and numerical methods, to form probability distributions for both discrete and continuous random variables, to learn sampling distribution and central limit theorem and to construct confidence intervals and apply hypothesis testing procedures.

Learning Outcomes of the Course Unit

1   Describe fundamental concepts of Statistics 2   Calculate descriptive statistics summarizing data sets 3   Calculate probabilities by probability functions of discrete and continuous random variables 4   Use sampling distributions 5   Apply central limit theorem 6   Construct confidence interval for various parameters 7   Test statistical hypothesis for various parameters

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 The Science of Statistics, Types of Statistical Applications, Fundemantal Elements of Statistics, Types of Data, Collecting Data 3 Numerical Measures for Central Tendency 4 Numerical Measures for Variability, Numerical measures for Relative Standing 5 Sample Spaces and Events, Unions and Intersections, Complementary Events, Additive Rule and Mutually Exclusive Events 6 Discrete Random Variables, Probability Distributions 7 Continuous Random Variables, Probability Density Functions 8 The Discrete Uniform Distribution, Bernoulli Distribution, The Binomial Distribution, Poisson Distribution 9 The Normal Distributions, The Normal Approximation to the Binomial Distribution, Exponential Distribution 10 Midterm Exam 11 What is Sampling Distribution , The Central Limit Theorem 12 Large and Sample Confidence Intervals for a Population Mean and Hypothesis Testing 13 Large Sample Confidence Interval for Two Population Means, Large Sample Test of Hypothesis About a Population Proportion, Large Sample Test of Hypothesis About a Population Variance and Hypothesis Testing 14 Large Sample Confidence Interval for Two Population Proportions, Large Sample Confidence Interval for Two Population Variances and Hypothesis Testing

Recomended or Required Reading

Probability and Statistics in Engineering and Management Science. Third Edition.(1990) Williem W. Hines, Douglas C. Monthgomery. Wiley&Sons

Planned Learning Activities and Teaching Methods

Lecture, homework assignments, problem solving

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 ASG ASSIGNMENT 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE * 0.40 + ASG * 0.10 + FIN * 0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + ASG * 0.10 + RST * 0.50 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 2 26 Tutorials 14 2 28 Preparations before/after weekly lectures 13 1 13 Preparation for midterm exam 1 12 12 Preparation for final exam 1 12 12 Preparing assignments 2 4 8 Midterm 1 2 2 Final 1 2 2 TOTAL WORKLOAD (hours) 103

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 LO.1 5 3 4 3 LO.2 5 3 4 3 LO.3 5 3 4 3 LO.4 3 3 4 3 LO.5 5 3 4 3 LO.6 3 3 4 3 LO.7 3 3 4 3