Psychology
Bachelor	Length of the Programme: 4	Number of Credits: 240	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF: Level 6

Ders Genel Tanıtım Bilgileri

School/Faculty/Institute

Faculty of Econ., Admin. and Social Sciences

Course Code

MATH 126

Course Title in English

Statistics for Social Sciences

Course Title in Turkish

Sosyal Bilimler için İstatistik

Language of Instruction

Type of Course

Exercise,Flipped Classroom,Laboratory Work,Lecture,Practical

Level of Course

Introductory

Semester

Spring

Contact Hours per Week

Lecture: 2

Recitation:

Lab: 1

Other:

Estimated Student Workload

146 hours per semester

Number of Credits

6 ECTS

Grading Mode

Standard Letter Grade

Pre-requisites

None

Expected Prior Knowledge

None

Co-requisites

None

Registration Restrictions

Only Undergraduate Students

Overall Educational Objective

To learn the basic statistical concepts with on hands applications using modern tools to summarize and analyze data via graphical and quantitative tools, to learn to drive conclusions using statistical analysis and modern tools.

Course Description

The aim of the course is to give the fundamentals of statistical analysis. This course introduces the basics of statistics for social sciences to summarize numerical and categorical data obtained from surveys, experiments, etc. The topics include different data types, measures of location, variability, shape, and association between variables. The students are expected to learn the fundamental concepts of hypothesis testing and locate apply appropriate tests for population mean, proportion, and difference, independence, and goodness to fit. Students will be able to apply Analysis of Variance and Simple Linear Regression using modern tools.

Course Description in Turkish

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
1) summarize numerical and categorical data by frequency distribution, histograms, and computing descriptive statistics (mean, median, variance) by hand and\or using excel;
2) analyze and interpret association between two variables using covariance and correlation coefficient by hand and/or using excel;
3) understand the basic concepts of hypothesis testing (type I and II errors), explain the differences among various statistical techniques and identify an appropriate technique for a given set of variables and research questions;
4) design, solve and interpret the results of hypothesis tests (t-test, z-test) related to population mean, population proportion, population differences;
5) design, solve and interpret the results of hypothesis tests (chi-square test) related to goodness to fit and tests of independence;
6) design, solve and interpret the results of Analysis of Variance (ANOVA) to compare population means;
7) analyze numerical data by graphs, create and test the validity of a simple linear regression model using excel, and to understand the use of regression models in prediction and estimation.

Program Learning Outcomes/Course Learning Outcomes	1	2	3	4	5	6	7
1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology.
2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation.
3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes.
4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts.
5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline.
6) Internalization and dissemination of professional ethical standards.
7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences.
8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level).
9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity.
10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement.
11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses.
12) Ability to acquire knowledge independently, and to plan one’s own learning.
13) Demonstration of advanced competence in the clarity and composition of written work and presentations.

Relation to Program Outcomes and Competences

N None	S Supportive	H Highly Related

	Program Outcomes and Competences	Level	Assessed by
1)	Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology.	N
2)	Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation.	S	Exam
3)	Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes.	H	Exam,HW,Project
4)	Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts.	S	Exam,HW,Project
5)	Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline.	N
6)	Internalization and dissemination of professional ethical standards.	S	Exam,HW,Project
7)	Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences.	H	Exam,HW,Project
8)	Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level).	N
9)	Recognition, understanding, and respect for the complexity of sociocultural and international diversity.	N
10)	Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement.	S	HW
11)	Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses.	H	Exam,Project
12)	Ability to acquire knowledge independently, and to plan one’s own learning.	N
13)	Demonstration of advanced competence in the clarity and composition of written work and presentations.	N

Prepared by and Date	BANU FEMİR GÜRTUNA , November 2023
Course Coordinator	YALCIN AKIN DUYAN
Semester	Spring
Name of Instructor	Asst. Prof. Dr. BANU FEMİR GÜRTUNA

Course Contents

Week	Subject
1)	1. Data and Statistics 1.1Data, Data Types, Sources of Data 2. Descriptive statistics 2.1Summarizing data for Categorical variables
2)	2.Descriptive Statistics 2.2 Summarizing data for Quantitative variables 2.3 Summarizing data for two variables 2.4 Measures of location Quiz 1 (on summarizing data)
3)	2. Descriptive Statistics 2. 4 Measures of location 2.5 Measures of variability
4)	2. Descriptive Statistics 2.6 Measures of distribution Shape 2.7 Box plots Quiz 2 (on measures of locality and variability)
5)	2. Descriptive Statistics 2.8 Measures of Association between Two Variables 2.9 The Weighted Mean and Working with Grouped Data Quiz 3 (on grouped data and covariance, correlation)
6)	3. Hypothesis Testing 3.1 Null and alternative hypothesis 3.2 Type I and II Errors 3.3 Testing population mean, known variance Midterm I (on first 5 weeks)
7)	3. Hypothesis Testing 3.4 Testing population mean, unknown variance 3.5 Testing population proportion
8)	3. Hypothesis Testing 3.6 Testing population differences Quiz 4 (on testing population mean and proportion)
9)	3. Hypothesis Testing 3.7 Goodness to Fit test and Testing independence Quiz 5 (on goodness to fit)
10)	4. Analysis of Variance
11)	4. Analysis of Variance Midterm II (on first 10 weeks)
12)	5. Simple Linear Regression Quiz 6 (on ANOVA)
13)	5. Simple Linear Regression Quiz 7 (on Simple Linear Regression)
14)	6. Review on deciding the appropriate tests for different problems Quiz 8 (on Regression)
15)	Final Examination Period
16)	Final Examination Period

Required/Recommended Readings

Modern Business Statistics with Microsoft Excel by David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, 5th edition. Stats: Modeling the World (4th edition) by David E. Bock, Paul F. Velleman, Richard D. De Veaux, Pearson. Applied Statistics for Social and Management Sciences by Abdul Quader Miah, Springer.

Teaching Methods

Flipped classroom/ laboratory

Homework and Projects

Laboratory Work

Computer Use

Students will apply the methods they learned using excel at the laboratory hours.

Other Activities

Assessment Methods

Assessment Tools	Count	Weight
Attendance	1	% 10
Quiz(zes)	5	% 20
Midterm(s)	2	% 30
Final Examination	1	% 40
TOTAL		% 100

Course Administration

femirb@mef.edu.tr

Attendance: All students are expected to attend the lectures according to the university regulations. Grading and Evaluation: The course will be instructed by Tuna Çakar. Only the best five of the eight quizzes will be taken into account. Students are required to achieve 30% of success rate in order to enter the final exam. Academic Integrity: All students of MEF University are expected to be honest and comply with academic integrity. Students are expected to do their own work and neither give nor receive unauthorized assistance. Disciplinary action will be taken for any cheating suspicion/action. Academic dishonesty and plagiarism: YÖK Disciplinary Regulation.

ECTS Student Workload Estimation

Activity	No/Weeks	Hours			Calculation
	No/Weeks per Semester	Preparing for the Activity	Spent in the Activity Itself	Completing the Activity Requirements
Course Hours	14	3	3	1	98
Project	7	2			14
Midterm(s)	2	7	2		18
Final Examination	1	14	2		16
Total Workload					146
Total Workload/25					5.8
ECTS					6