School/Faculty/Institute Faculty of Economics, Administrative 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 EN
Type of Course Exercise,Lecture,Laboratory Work,Practical,Flipped Classroom
Level of Course Introductory
Semester Spring
Contact Hours per Week
Lecture: 3 Recitation: 0 Lab: 0 Other: 0
Estimated Student Workload 146 hours per semester
Number of Credits 6 ECTS
Grading Mode Standard Letter Grade
Pre-requisites None
Co-requisites None
Expected Prior Knowledge 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 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 BANU FEMİR GÜRTUNA
Semester Spring
Name of Instructor Asst. Prof. Dr. YALCIN AKIN DUYAN

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
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
9) 3. Hypothesis Testing 3.7 Goodness to Fit test and Testing independence
10) 4. Analysis of Variance
11) 4. Analysis of Variance II
12) 5. Simple Linear Regression
13) 5. 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 ReadingsModern 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 MethodsFlipped classroom/ laboratory
Homework and ProjectsMidterm & final exam
Laboratory WorkNone
Computer UseUsing basic excel.
Other ActivitiesNone
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

Throughout the semester, students are responsible for following announcements, working on the uploaded material and responding to the discussions on the blackboard on a weekly basis. Coming class prepared is compulsory to be able to follow the course and stay engaged within the class. Students can submit a paper assignment on a rescheduled date and take make-up exams only if they submit an official health report to the faculty secretary’s office. The format of the make-up exams might differ from the exam delivered on time. Students are expected to come to class on time and be respectful of the teaching and learning environment at all times. Academic dishonesty will not be tolerated and is strictly penalized. Academic dishonesty includes any commitment of cheating, lying and deceit in any form such as plagiarism or cheating during exams. Students are strictly responsible for submitting their own work, not that of others or other agents. Full citation of others’ work is required. 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
Quiz(zes) 2 7 14
Midterm(s) 2 7 2 18
Final Examination 1 14 2 16
Total Workload 146
Total Workload/25 5.8
ECTS 6