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Course Description Course Name : Data Collection and Analysis Course Code : İM-578 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Spring (16 Weeks) ECTS : 6 Name of Lecturer(s) : Prof.Dr. EMEL ORAL LAPTALI Learning Outcomes of the Course : Knows data analysis, hypothesis testing Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : It is aimed to teach the process of data collection and analysis. Course Contents : Data analysis Language of Instruction : Turkish Work Place : Lecture room   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Introduction to statistics Reading Lecture 2 Data collection methods Reading Lecture 3 Data clustering Reading Lecture 4 Descriptive statistics Reading Lecture 5 Descriptive statistics Reading Lecture 6 Mid term exam 1 Reading Exam 7 Correlation, regression Reading Lecture 8 Problem solving Reading, problem solving Lecture 9 Parametric tests Reading, problem solving Lecture 10 Non parametric tests Reading, problem solving Lecture 11 Mid term 2 Reading, problem solving Exam 12 SPSS Applications SPSS practice Lecture and SPSS applications 13 SPSS Applications SPSS practice Lecture and SPSS applications 14 SPSS Applications SPSS practice Lecture and SPSS applications 15 SPSS Applications SPSS practice Lecture and SPSS applications 16/17 Final Exam Reading, problem solving Exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Statistics books Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 2 50     Homeworks/Projects/Others 3 50 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Have knowledge and understanding at advanced level providing required basis for original projects in the field of civil engineering based on qualifications gained at undergraduate level. 5 2 Gain required knowledge through scientific research in the field of engineering, evaluate, interpret and apply data. 4 3 Be aware of new and emerging applications,examine and learn where necessary. 5 4 Construct engineering problems, develop strategies to solve them, and apply innovative methods for solutions. 0 5 Design and implement analytical modeling and experimental research and solve complex situations encountered in this process 0 6 Develop new and / or original ideas and methods; develop innovative solutions for the system, part, and process design. 3 7 Have learning skills 4 8 Be aware of innovative developments in the field of civil engineering, and analyse and learn them when needed. 5 9 Transfer process and results of the projects in the field of civil engineering or on national and international platforms in written or oral form. 2 10 Have knowledge in current techniques and methods applied in civil engineering. 5 11 Use computer software as well as information and communication technologies at the level required in the field of civil engineering 4 12 Oversee social, scientific and ethical values in all professional platforms. 5 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 3 42 Assesment Related Works     Homeworks, Projects, Others 3 15 45     Mid-term Exams (Written, Oral, etc.) 2 5 10     Final Exam 1 5 5 Total Workload: 144 Total Workload / 25 (h): 5.76 ECTS Credit: 6