# GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
STATISTICS AND SMART APPROACHES/İST2043
 Course Title: STATISTICS AND SMART APPROACHES Credits 2 ECTS 3 Course Semester 3 Type of The Course Elective
COURSE INFORMATION
-- (CATALOG CONTENT)
-- (TEXTBOOK)
-- (SUPPLEMENTARY TEXTBOOK)
-- (PREREQUISITES AND CO-REQUISITES)
-- LANGUAGE OF INSTRUCTION
Turkish
-- COURSE OBJECTIVES
-- COURSE LEARNING OUTCOMES
Learns the need for Smart approaches based on basic statistics concepts.
Knows Smart approach methods.
Learns the classical data sources and social media as a data source.
In the future editing, in the light of Smart approaches, experience a look at the Science of Statistics again.

-- MODE OF DELIVERY
The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE 1. Week Statistics and the subject of Statistics 2. Week The emergence of intelligent approaches 3. Week Data structures and data science 4. Week What is the next big step in statistics? 5. Week Intelligent approximation methods 6. Week Big Data 7. Week Data Mining 8. Week Other Approaches, Midterm 9. Week Data sources 10. Week Management, Planning and Economics 11. Week Stock Exchange and Finance 12. Week Science, Engineering and Technology 13. Week Social media as data source 14. Week In the light of the smart approaches, in the editing of the future 15. Week Final Exam 16. Week
-- TEACHING and LEARNING METHODS
-- ASSESSMENT CRITERIA
 Quantity Total Weighting (%) Midterm Exams 1 25 Assignment 0 0 Application 0 0 Projects 1 15 Practice 0 0 Quiz 0 0 Percent of In-term Studies 40 Percentage of Final Exam to Total Score 60
 Activity Total Number of Weeks Duration (weekly hour) Total Period Work Load Weekly Theoretical Course Hours 14 2 28 Weekly Tutorial Hours 0 Reading Tasks 3 2 6 Searching in Internet and Library 4 2 8 Material Design and Implementation 0 Report Preparing 3 2 6 Preparing a Presentation 2 2 4 Presentation 1 2 2 Midterm Exam and Preperation for Midterm Exam 1 10 10 Final Exam and Preperation for Final Exam 1 10 10 Other (should be emphasized) 0 TOTAL WORKLOAD: 74 TOTAL WORKLOAD / 25: 2.96 Course Credit (ECTS): 3
-- COURSE'S CONTRIBUTION TO PROGRAM
 NO PROGRAM LEARNING OUTCOMES 1 2 3 4 5 1 1. The statistical textbooks which include latest information about statistics, equipment and other resources supported by scientific approach on undergraduate level have theoretical and practical knowledge. X 2 2. Statisticians by using knowledge and skills acquired at bachelor degree level model, analyze, and interpret datasets. X 3 3. Statisticians identify and analyze the problems with current developments in statistic and also develop solutions based upon researches and proofs. X 4 4. Statisticians apply theoretical and practical knowledge acquired in Statistics at bachelor degree level to the current problems. X 5 5. Statisticians have the ability to use computer software and computing technology at the certain level required by statistics field. X 6 6. Statisticians take responsibility at disciplinary and interdisciplinary studies as an individual or a team member. X 7 7. Statisticians must have knowledge and ability to follow development in the field of Statistics, and must develop life long-learning attitudes. X 8 8. By using a foreign language, statistician can keep track of every statistical information, and communicate with colleagues. X 9 9. Applying the statistical knowledge in the professional sense, statistician has social, scientific, and ethical values. X 10 10. A statistician must have the ability to social sensitivity and socialization. X 11 11. During the process of inference, a statistician uses time efficiently with the analytical thinking ability. X
-- NAME OF LECTURER(S)
(Prof.Dr. Reşat KASAP)
-- WEB SITE(S) OF LECTURER(S)
(https://abs.gazi.edu.tr/rkasap)
-- EMAIL(S) OF LECTURER(S)
(rkasap@gazi.edu.tr)