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Course Description Course Name : Statistical Package Programs Course Code : İSB334 Course Type : Compulsory Level of Course : First Cycle Year of Study : 3 Course Semester : Spring (16 Weeks) ECTS : 6 Name of Lecturer(s) : Assoc.Prof.Dr. GÜZİN YÜKSEL Learning Outcomes of the Course : This course gives students the ability to analyze data and information skills. Be able to find solutions to the problems of operational work. Students learn how to use SPSS. Students gain the ability to analyze data with SPSS. Be able to apply statistics structures using SPSS in a business environment. Develops the skills in problem analysis and problem solving Develops the skills in data handling and manipulation Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : The purpose of this course, in different fields, basic statistical methods used in the SPSS data analysis program are processed on the theoretical and practical manner, the student be able to comment, analysis on issues like the ability to gain skills. Course Contents : Introduction to basic computer skills, Preparation of data, Descriptive Statistics, Correlation, Statistical Tests, ANOVA Analysis, Regression Analysis, Coding survey data, Reliability Analysis Language of Instruction : Turkish Work Place : Laboratory   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Introduction to basic computer skills Reading source and application Presentations, applications, comments and class discussions 2 Introduction to SPSS Program Reading source and application Presentations, applications, comments and class discussions 3 Preparation of data Reading source and application Presentations, applications, comments and class discussions 4 Data screening and transformation Reading source and application Presentations, applications, comments and class discussions 5 Descriptive Statistics Reading source and application Presentations, applications, comments and class discussions 6 Correlation Reading source and application Presentations, applications, comments and class discussions 7 Tests for means Reading source and application Presentations, applications, comments and class discussions 8 Midterm Review the topics discussed in the lecture notes and sources Written exam 9 Statistical Tests Reading source and application Presentations, applications, comments and class discussions 10 ANOVA Analysis Reading source and application Presentations, applications, comments and class discussions 11 ANOVA Analysis Reading source and application Presentations, applications, comments and class discussions 12 Regression Analysis Reading source and application Presentations, applications, comments and class discussions 13 Regression Analysis Reading source and application Presentations, applications, comments and class discussions 14 Coding survey data Reading source and application Presentations, applications, comments and class discussions 15 Reliability Analysis Reading source and application Presentations, applications, comments and class discussions 16/17 Final Exam Review the topics discussed in the lecture notes and sources Written exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  SPSS Paket Programı İle İstatistiksel Veri Analizi, Prof.Dr. Hamza Erol, Nobel Kitabevi, 2010, Adana. Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 60     Homeworks/Projects/Others 5 40 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 Utilize computer systems and softwares 5 2 Apply the statistical analyze methods 5 3 Make statistical inference(estimation, hypothesis tests etc.) 5 4 Generate solutions for the problems in other disciplines by using statistical techniques 5 5 Discover the visual, database and web programming techniques and posses the ability of writing programme 5 6 Construct a model and analyze it by using statistical packages 5 7 Distinguish the difference between the statistical methods 5 8 Be aware of the interaction between the disciplines related to statistics 5 9 Make oral and visual presentation for the results of statistical methods 5 10 Have capability on effective and productive work in a group and individually 5 11 Develop scientific and ethical values in the fields of statistics-and scientific data collection 4 12 Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics 5 13 Emphasize the importance of Statistics in life 5 14 Define basic principles and concepts in the field of Law and Economics 3 15 Produce numeric and statistical solutions in order to overcome the problems 4 16 Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events 5 17 Use proper methods and techniques to gather and/or to arrange the data 5 18 Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs 1 * 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 5 6 30     Mid-term Exams (Written, Oral, etc.) 1 10 10     Final Exam 1 20 20 Total Workload: 144 Total Workload / 25 (h): 5.76 ECTS Credit: 6