SOFTWARE ENGINEERING
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
ECO2062	Applied Statistics	Fall	3	0	3	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Hybrid
Course Coordinator :	Dr. Öğr. Üyesi SERKAN YEŞİLYURT
Course Lecturer(s):	Dr. Öğr. Üyesi AYSE ERTUĞRUL BAYKAN Prof. Dr. İPEK ALTINBAŞAK FARİNA
Recommended Optional Program Components:	None
Course Objectives:	To apply and interpret the results of a variety of statistical techniques from both descriptive and inferential statistics

Learning Outcomes

The students who have succeeded in this course;
1. The concept of the sampling distribution and to compute probabilities related to the sample mean and the sample proportion

2. To construct and interpret confidence interval estimates for the mean and the proportion

3. The basic principles of hypothesis testing and how to use hypothesis testing to test a mean or proportion

4. How to use hypothesis testing for comparing the difference between the means and proportion of populations

5. How to use one-way and two-way analysis of variance to test for differences among the means of several populations

6. How and when to use the chi-square test for contingency tables and how to use the chi-square test for a variance or standard deviation

7. How to use regression analysis to investigate the relationship between variables.

Course Content

Sampling and Sampling Distributions

Sampling Distribution Properties

Point and Interval Estimates
Confidence Interval for population mean

Confidence Intervals for the
Population Proportion, π
Fundamentals of Hypothesis Testing: One-Sample Tests
Hypothesis Testing for Mean and Proportion
Two-Sample Tests for Mean

Two-Sample Tests for Proportion

One-Way Analysis of Variance

Two-Way Analysis of Variance

Chi-Square Tests and Nonparametric Tests

Introduction to Simple Linear Regression

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Sampling and Sampling Distributions
2)	Point and Interval Estimates
3)	Sampling Distribution Properties
4)	Confidence Interval for population mean
5)	Confidence Intervals for the Population Proportion, π
6)	Fundamentals of Hypothesis Testing: One-Sample Tests
7)	Hypothesis Testing for Mean and Proportion
8)	Review
9)	Two-Sample Tests for Mean
10)	Two-Sample Tests for Proportion
11)	Analysis of Variance
12)	Chi-Square Tests and Nonparametric Tests
13)	Introduction to Simple Linear Regression
14)	Review

Sources

Course Notes / Textbooks:	Basic Business Statistics Concepts and Applications Mark L. Brenson, David M. Levine, Timothy C. Krehbiel, Pearson Education Prentice Hal.
References:	.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	4	% 20
Midterms	1	% 35
Final	1	% 45
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 55
PERCENTAGE OF FINAL WORK		% 45
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	16	3	48
Study Hours Out of Class	14	7	98
Midterms	1	2	2
Final	1	2	2
Total Workload			150

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Be able to specify functional and non-functional attributes of software projects, processes and products.
2)	Be able to design software architecture, components, interfaces and subcomponents of a system for complex engineering problems.
3)	Be able to develop a complex software system with in terms of code development, verification, testing and debugging.
4)	Be able to verify software by testing its program behavior through expected results for a complex engineering problem.
5)	Be able to maintain a complex software system due to working environment changes, new user demands and software errors that occur during operation.
6)	Be able to monitor and control changes in the complex software system, to integrate the software with other systems, and to plan and manage new releases systematically.
7)	Be able to identify, evaluate, measure, manage and apply complex software system life cycle processes in software development by working within and interdisciplinary teams.
8)	Be able to use various tools and methods to collect software requirements, design, develop, test and maintain software under realistic constraints and conditions in complex engineering problems.
9)	Be able to define basic quality metrics, apply software life cycle processes, measure software quality, identify quality model characteristics, apply standards and be able to use them to analyze, design, develop, verify and test complex software system.
10)	Be able to gain technical information about other disciplines such as sustainable development that have common boundaries with software engineering such as mathematics, science, computer engineering, industrial engineering, systems engineering, economics, management and be able to create innovative ideas in entrepreneurship activities.
11)	Be able to grasp software engineering culture and concept of ethics and have the basic information of applying them in the software engineering and learn and successfully apply necessary technical skills through professional life.
12)	Be able to write active reports using foreign languages and Turkish, understand written reports, prepare design and production reports, make effective presentations, give clear and understandable instructions.
13)	Be able to have knowledge about the effects of engineering applications on health, environment and security in universal and societal dimensions and the problems of engineering in the era and the legal consequences of engineering solutions.