STATISTICS II PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
EKF228	STATISTICS II	4	3	3	6

GENERAL INFORMATION
Language of Instruction :	Turkish
Level of the Course Unit :	BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course :	Compulsory
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Assist.Prof. DİDEM TETİK KÜÇÜKELÇİ
Instructor(s) of the Course Unit	Assist.Prof. DİDEM TETİK KÜÇÜKELÇİ
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	The aim of this course is to enable students to understand sampling- and probability-based statistical inference approaches and to develop the ability to apply fundamental statistical methods such as parameter estimation, confidence intervals, and hypothesis testing. In addition, the course aims to examine relationships between variables through correlation and simple linear regression analysis, and to interpret data by conducting trend analysis in time series. Students are expected to accurately interpret statistical results and use them in decision-making processes.
Contents of the Course Unit:	This course covers sampling methods, sampling distributions and the Central Limit Theorem, point and interval estimation (confidence intervals), hypothesis testing (z and t tests), two-sample tests, chi-square tests, one-way analysis of variance (ANOVA), correlation analysis, simple linear regression analysis, as well as an introduction to time series and trend analysis. The course is supported not only by theoretical instruction but also by sample problem solving and applied analyses.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Defines and explains sampling methods and sampling distributions.

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	Literature reading, assignment	Introduction to sampling methods and sampling distributions	Lecture, problem solving
2	Literature reading, assignment	Central Limit Theorem and its applications	Lecture, problem solving
3	Literature reading, assignment	Point estimation: estimators and their properties	Lecture, problem solving
4	Literature reading, assignment	Interval estimation (confidence intervals): mean and proportion	Lecture, problem solving
5	Literature reading, assignment	Fundamentals of hypothesis testing (H0–H1, errors, p-value	Lecture, problem solving
6	Literature reading, assignment	One-sample hypothesis tests (Z test, t test	Lecture, problem solving
7	Literature reading, assignment	Two-sample hypothesis tests (independent samples t test)	Lecture, problem solving
8	Literature reading, assignment	Paired-samples t test and applications	Lecture, problem solving
9	Literature reading, assignment	Chi-square (χ²) tests: goodness-of-fit and independence tests	Lecture, problem solving
10	-	MID-TERM EXAM	-
11	Literature reading, assignment	One-way analysis of variance (ANOVA) and post-hoc tests	Lecture, problem solving
12	Literature reading, assignment	Correlation analysis (Pearson) and interpretation	Lecture, problem solving
13	Literature reading, assignment	Simple linear regression: model building and interpretation	Lecture, problem solving
14	Literature reading, assignment	Introduction to time series and trend analysis (moving average, linear trend)	Lecture, problem solving
15	Literature reading, assignment	Introduction to time series and trend analysis (moving average, linear trend)	Lecture, problem solving
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
olasılık ve istatistik-Fikri AKdeniz

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description	Examination Method
Mid-Term Exam	1	50		Classical Exam
Final Exam	1	50		Classical Exam
TOTAL	2	100

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Define concepts such as management, manager and leader.				3
2	Analyze the accuracy, reliability and validity of the new information obtained from the data.				3

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Report the obtained data.				3
2	Prepare software and projects related with the field.				3

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Use the appropriate resources for data analysis related with the field.				3
2	Analyze the work processes.				3

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Manage projects as part of a team.				3
2	Apply the material, techniques and analyzes in relation with the subject for project and work flows.				3

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Fulfill responsibility with a focus on result in individual and team studies.				3

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Recognizes what he/she knows about his/her field or not.				3
2	Act the theoretical knowledge in real life with learning to learn approach.				3
3	Apply different methods and techniques with an innovative approach in his/her research.				3

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Apply the results obtained in accordance with voluntarism and social responsibility projects.				3
2	Establish a healthy contact with colleagues				3
3	Share the analyzes and obtained results with colleagues.				3
4	Cooperate with colleagues at international level with the help of foreign language competency.				3

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Behave in accordance with ethical values regarding the collection, analysis and reporting of data.				3
2	Participate the design of work processes and systems with full quality.				3
3	Cooperate with other employees for the continuation of sustainability in the profession.				3

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	3	42
Preliminary & Further Study	14	8	112
Land Surveying	0	0	0
Group Work	0	0	0
Laboratory	0	0	0
Reading	0	0	0
Assignment (Homework)	0	0	0
Project Work	0	0	0
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	0	0	0
Final Exam	1	1	1
Preparation for the Final Exam	0	0	0
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	0	0	0
Short Exam	0	0	0
Preparation for the Short Exam	0	0	0
TOTAL	30	0	156