PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
YBS 224	INTRODUCTION TO INFERENTIAL STATISTICS	3 + 0	4th Semester	4

COURSE DESCRIPTION

Course Level	Bachelor's Degree
Course Type	Compulsory
Course Objective	The purpose of this course is to provide students with the necessary knowledge on inferential statistics in order to make them conscious consumers of scientific studies and to help them grasp the fundamentals of statistics for conducting data analyses in software project and information systems.
Course Content	Sampling Distribution, Hypothesis Testing, Interval Estimation, Data Mining and SPSS Applications, Regression and Correlations Analysis in Big Data
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	Able to think analytically on big data based
2	Able generalize statistical findings properly
3	Able think probabilistically in information projects
4	Able to use SPSS for statistical analysis

COURSE'S CONTRIBUTION TO PROGRAM

	PO 01	PO 02	PO 03	PO 04	PO 05	PO 06	PO 07	PO 08	PO 09	PO 10	PO 11	PO 12
LO 001					1	1	4	3	5	4	3	5
LO 002				1		2	4	3	5	5	3	5
LO 003							4	4	4	3	5	5
LO 004							3	3	3	4	5	3
Sub Total				1	1	3	15	13	17	16	16	18
Contribution	0	0	0	0	0	1	4	3	4	4	4	5

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Hours for off-the-classroom study (Pre-study, practice)	14	3	42
Mid-terms	1	8	8
Final examination	1	12	12
Total Work Load ECTS Credit of the Course			104 4

COURSE DETAILS

Select Year

Course Details

Course Code	Course Title	L+P Hour	Course Code	Language Of Instruction	Course Semester
YBS 224	INTRODUCTION TO INFERENTIAL STATISTICS	3 + 0	2	Turkish	2023-2024 Spring

Course Coordinator	E-Mail	Phone Number	Course Location	Attendance
Asts. Prof. Dr. SERKAN DOLMA	dolma@pau.edu.tr		İİBF B0214	%

Goals		The purpose of this course is to provide students with the necessary knowledge on inferential statistics in order to make them conscious consumers of scientific studies and to help them grasp the fundamentals of statistics for conducting data analyses in software project and information systems.
Content		Sampling Distribution, Hypothesis Testing, Interval Estimation, Data Mining and SPSS Applications, Regression and Correlations Analysis in Big Data

Topics

Materials

Materials are not specified.

Resources

Course Assessment

L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

Prospective Student