| School/Faculty/Institute | Faculty of Education | |||||
| Course Code | MATH 234 | |||||
| Course Title in English | Statistics II | |||||
| Course Title in Turkish | Statistics II | |||||
| Language of Instruction | EN | |||||
| Type of Course | Flipped Classroom,Lecture | |||||
| Level of Course | Introductory | |||||
| Semester | Spring | |||||
| Contact Hours per Week |
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| Estimated Student Workload | 130 hours per semester | |||||
| Number of Credits | 5 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 concepts and procedures in descriptive and inferential statistics. | |||||
| Course Description | This course covers the basic concepts and procedures in descriptive and inferential statistics. As a follow up of MATH 233 Statistics I course, this course begins with the review of basic concepts such as standard deviation, standardized scores (i.e., z-scores), standard error, the distribution of sample means, and probability and normal distribution. The course will continue with the methods for hypothesis testing and describing relationships between two (or more) variables, t-statistic, the t-test for the two independent and related samples, estimation, analysis of variance test for differences among two or more population means (ANOVA), correlations, and nonparametric tests. | |||||
| Course Description in Turkish | Bu ders, tanımlayıcı ve çıkarımsal istatistikteki temel kavramları ve prosedürleri kapsar. MATG233 İstatistik I dersinin devamı niteliğinde olan bu ders, standart sapma, standartlaştırılmış puanlar (yani, z puanları), standart hata, örnek ortalamaların dağılımı ve olasılık ve normal dağılım gibi temel kavramların gözden geçirilmesiyle başlar. Ders, hipotez testi ve iki (veya daha fazla) değişken arasındaki ilişkileri tanımlama yöntemleri, t-istatistiği, iki bağımsız ve ilgili örnek için t-testi, tahmin, iki veya daha fazla popülasyon arasındaki farklar için varyans analizi (ANOVA), korelasyonlar ve parametrik olmayan testlerle devam edecektir.. |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) appreciate the importance of statistics and data analysis 2) understand the basics of hypothesis testing; 3) understand and apply the non-directional and directional hypothesis testing techniques 4) understand the concept of analysis of variance test for differences among two or more population means (ANOVA); 5) understand and apply correlation and regression techniques 6) understand some non-parametric tests such as the concept of chi-square statistic |
| Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
| 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. |
| 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. | N | |
| 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,Participation |
| 4) | Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | N | |
| 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. | N | |
| 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. | N | |
| 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. | S | Participation |
| 10) | Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | S | HW,Participation |
| 11) | Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | N | |
| 12) | Ability to acquire knowledge independently, and to plan one’s own learning. | S | Exam,HW |
| 13) | Demonstration of advanced competence in the clarity and composition of written work and presentations. | H | Exam,HW |
| Prepared by and Date | MAHMUT KERTİL , |
| Course Coordinator | BENGİ BİRGİLİ |
| Semester | Spring |
| Name of Instructor | Asst. Prof. Dr. MAHMUT KERTİL |
| Week | Subject |
| 1) | Introduction to the course Reviewing the basic concepts |
| 2) | Introduction to Hypothesis Testing: The Logic of Hypothesis Testing |
| 3) | Directional Hypothesis Testing Statistic Lab: Using MsExcel or SPSS |
| 4) | Introduction to the t statistic Hypothesis tests with the t statistic |
| 5) | The t-test for two independent samples (Statistic Lab: Using MsExcel or SPSS) |
| 6) | The t-test for two related samples |
| 7) | The t-test for two related samples (cont’d.) Statistic Lab: Using MsExcel or SPSS |
| 8) | Introduction to Analysis of Variance (ANOVA) |
| 9) | Introduction to Analysis of Variance (ANOVA) |
| 10) | Repeated-Measures Analysis of Variance |
| 11) | Two-Factor Analysis of Variance |
| 12) | Correlation & Introduction to Regression |
| 13) | Nonparametric tests: The Chi-Square Statistic |
| 14) | Nonparametric tests |
| 15) | Final Examination Period |
| 16) | Final Examination Period |
| Required/Recommended Readings | Gravetter, F. J. & Wallnau L. B. (2010). Essentials of Statistics for the Behavioral Sciences (9th ed.). Wadsworth, Cengage Learning. Shavelson, R.J. (1996). Statistical reasoning for the behavioral sciences (3rd ed.). Boston: Allyn & Bacon. | ||||||||||||||||||
| Teaching Methods | Flipped learning, Direct instruction, Group work on some classroom activities, Laboratory work | ||||||||||||||||||
| Homework and Projects | Students will be assigned four homework through the whole semester | ||||||||||||||||||
| Laboratory Work | Laboratory work will be held once in two weeks. In laboratory work, students are expected to use MsExcel or SPSS in order to apply the statistical concepts that they learned in the course. | ||||||||||||||||||
| Computer Use | Computer use is necessary during laboratory work. | ||||||||||||||||||
| Other Activities | In-class group works on some problems will be conducted. | ||||||||||||||||||
| Assessment Methods |
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| Course Administration |
kertilm@mef.edu.tr Dr. Mahmut Kertil e-mail: kertilm@mef.edu.tr Office Hours: by appointment Rules for attendance: The student must attend at least 70% of the classes. Academic dishonesty and plagiarism: YOK Disciplinary Regulation |
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| 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 | 1 | 3 | 1 | 70 | ||
| Project | 4 | 8 | 32 | ||||
| Midterm(s) | 1 | 8 | 2 | 10 | |||
| Final Examination | 1 | 16 | 2 | 18 | |||
| Total Workload | 130 | ||||||
| Total Workload/25 | 5.2 | ||||||
| ECTS | 5 | ||||||