COURSE UNIT TITLE

: INTRODUCTION TO STATISTICS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
BIL 1014 INTRODUCTION TO STATISTICS COMPULSORY 3 0 0 4

Offered By

Computer Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR EMEL KURUOĞLU KANDEMIR

Offered to

Computer Science

Course Objective

The purpose of this course is to introduce the students with the statistics and probability. This course emphasizes on describing the statistics, classifying data, calculating central tendency and variation measures, using tables and graphics, evaluating permutation, combination and probability, obtaining probability distributions for both discrete and continuous random variables and using some special probability distributions.

Learning Outcomes of the Course Unit

1   Describing fundamental elements of Statistics.
2   Distinguishing types of data.
3   Calculating the measures which are used for describing data. Tables and graphics. Applications.
4   Describing the fundamental elements of Probability and Calculating probabilities.
5   Calculating probabilities by probability functions of discrete and continuous random variables and Describing some special probability distributions.

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
2 Types of Data Collecting Data Describing Qualitative Data
3 Graphical Methods for Describing Quantitative Data Numerical Measures for Central Tendency Applications
4 Numerical Measures for Variability Numerical measures for Relative Standing
5 Combinatorial Methods Applications
6 Sample Spaces and Events Unions and Intersections Complementary Events Additive Rule and Mutually Exclusive Events
7 The Probability of an Event
8 Some Rules of Probability Conditional Probability
9 Independent Events and The Multiplicative Rule Bayes Theorem
10 Discrete Random Variables Probability Distributions
11 Continuous Random Variables Probability Density Functions
12 Some special discrete distributions (Binomial, Negative Binom, Geometrik, Hypergeometric, Poisson)
13 Some special continuous distributions (Uniform, Normal, Exponential) Applications
14 The Expected Value of Random Variable

Recomended or Required Reading

Textbook(s): 1) Freund, John E., Mathematical Statistics, 5th. Ed.Prentice Hall, 1992.
2) McClave, James T. and Sincich, Terry, Statistics, 8th. Ed., Prentice Hall, 2000.
3) Adil Oğuzhan, Aylin Alın, Deniz Inan, Dilek Altaş, Emel Kuruoğlu Kandemir, Ersin Kıral, Gülin Tabakan, Gülsen Kıral, Handan Yolsal, Latif Öztürk, Nazif Çalış, Özlem Akay, Özlem Türkşen, Özlem Yorulmaz, Seda Şengül, Istatistik (Excel, SPSS, R ve MATLAB Uygulamalı), Nobel Akademik Yayıncılık, ISBN: 978-625-406-758-7, Aralık, 2020.

Supplementary Book: 1) Bain, L.J. and Engelhardt, M., Introduction to Probability and Mathematical Statistics, 2nd Ed.,Duxbury Classic Series,1992.

Planned Learning Activities and Teaching Methods

Lecture and problem solving.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 VZ Vize
2 FN Final
3 BNS BNS VZ * 0.40 + FN * 0.60
4 BUT Bütünleme Notu
5 BBN Bütünleme Sonu Başarı Notu VZ * 0.40 + BUT * 0.60


Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of exams.

Language of Instruction

Turkish

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

E-posta: cagin.kandemir@deu.edu.tr
Tel: 0232 301 95 12
E-posta: emel.kuruoglu@deu.edu.tr
Tel: 0232 301 95 10

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 2 28
Preparation for midterm exam 1 15 15
Preparation for final exam 1 20 20
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 109

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13
LO.1445
LO.2445
LO.3445
LO.4445
LO.5445