MECHATRONICS 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)	Build up a body of knowledge in mathematics, science and Mechatronics Engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems.
2)	Identify, formulate, and solve complex Mechatronics Engineering problems; select and apply proper modeling and analysis methods for this purpose.
3)	Design complex Mechatronic systems, processes, devices or products under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose.
4)	Devise, select, and use modern techniques and tools needed for solving complex problems in Mechatronics Engineering practice; employ information technologies effectively.
5)	Design and conduct numerical or pysical experiments, collect data, analyze and interpret results for investigating the complex problems specific to Mechatronics Engineering.
6)	Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working on Mechatronics-related problems.
7)	Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing. Write and understand reports, prepare design and production reports, deliver effective presentations, give and receive clear and understandable instructions.
8)	Recognize the need for life-long learning; show ability to access information, to follow developments in science and technology, and to continuously educate oneself.
9)	Develop an awareness of professional and ethical responsibility, and behave accordingly. Be informed about the standards used in Mechatronics Engineering applications.
10)	Learn about business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development.
11)	Acquire knowledge about the effects of practices of Mechatronics Engineering on health, environment, security in universal and social scope, and the contemporary problems of Mechatronics engineering; is aware of the legal consequences of Mechatronics engineering solutions.