
Description of Individual Course UnitsCourse Unit Code  Course Unit Title  Type of Course Unit  Year of Study  Semester  Number of ECTS Credits  708002122016  APPLIED STATISTICS  Compulsory  2  4  3 
 Level of Course Unit  First Cycle  Objectives of the Course  The aim of this course is to help sociology students to be able to do statistical analyses on a field research data and to be able to read, understand and properly interpret the statistical findings  Name of Lecturer(s)  Göknur (Bostancı) Ege  Learning Outcomes  1  identifying the basis of statistical analyses applied in the social sciences  2  having knowledge on basic classifications like that of variable, research universe, and sampling types.  3  making right decisions on which statistical analyses appropriate for a research data  4  entering and analyzing data by using an statistical applications software  5  be able to read and interpret accurately the results of statistical analyses, tables and graphs  6  understanding the related terminology in English 
 Mode of Delivery  Face to Face  Prerequisites and corequisities  Competence in English: to be able to read, write, understand and speak in English  Recommended Optional Programme Components  The students are recommended to take previous course “Statistics” in first semester before attending the course.
The students are recommended to do further practices after the class and do further reading to get better understanding for developing their own thinking and being aware of different approaches on the course subjects
 Course Contents  The course content covers following subjects: introduction to applied statistics, basic terminology, theories and statisticians influential in the history of applied statistics. theory of probability, research universe and sample types; finite and infinite universes, randomness in sampling, random and nonrandom samples, central limit theorem, representative and unbiased sampling, calculating sample size, variable types (discrete/continuous, qualitative, quantitative, dependent/independent) data and data and scale types (nominal, ordinal, interval, ratio), significance, reliability and tolerance, parameters of a research universe, describing normal distribution, standard deviance, mean, median variance through illustrations, correlation, regression and multiple regression by examples, one way annova, two way annova with illustrations, cross tables and Chi square test with illustrations, SPSS data entry, defining values and variables, illustrative applications of specific statistical analyses, How to read, understand and evaluate results of statistical analyses ( number, percent, valid percent, cumulative percent in a frequency table, column percent, row percent, total percent in a cross table etc.)  Weekly Detailed Course Contents  
1  Introduction to applied statistics, definitions of basic terminology    2  Introducing theories and statisticians influential in the history of applied statistics. theory of probability    3  Research universe and sample types; finite and infinite universes, randomness in sampling, random and nonrandom samples, central limit theorem    4  Representative and unbiased sampling, calculating sample size    5  Variable types (discrete/continuous, qualitative, quantitative, dependent/independent) data and data and scale types (nominal, ordinal, interval, ratio)    6  Significance, reliability and tolerance    7  Parameters of a research universe, describing normal distribution, standard deviance, mean, median variance through illustrations    8  MidTerm Exam    9  Correlation, regression and multiple regression by examples    10  One way annova, two way Annova with illustrations    11  Cross Tables and Chi Square test with illustrations    12  SPSS Data entry, defining values and variables    13  Missing Values, recoding, weighting    14  Illustrative applications of specific statistical analyses    15  How to read, understand and evaluate results of statistical analyses ( number, percent, valid percent, cumulative percent in a frequency table, column percent, row percent, total percent in a cross table etc    16  Final Exam   
 Recommended or Required Reading  Ozkan Unver , Hamza Gamgam, Uygulamali Istatistiksel yontemler, Siyasal Kitabevi 1996
Darrel Huff, Istatistik ve Istatistikle Nasil Yalan Soylenir, Cen :Engin Koparan, Sarmal Yayinevi , 2002
Seref Kalayci (Ed) SPSS Uygulamali Cok Degiskenli Istatistik Teknikleri, Asil Yayin 2005.
Yahsi Yazicioglu, Samiye Erdogan, SPSS Uygulamali bilimsel Arastirma yontemleri, Detay Yayincilik, 2004
Burhan Cil, Istatistik, Detay Yayincilik, 2005.
Fazil Guler, Temel Istatistik, Beta yayim, 2007
 Planned Learning Activities and Teaching Methods  Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"  Assessment Methods and Criteria   Language of Instruction  English  Work Placement(s)  None 
 Workload Calculation 

Midterm Examination  1  1  1  Final Examination  1  1  1  Attending Lectures  14  2  28  Practice  14  1  14  QuestionAnswer  15  1  15  Self Study  10  1  10  Individual Study for Mid term Examination  1  10  10  Individual Study for Final Examination  2  10  20  
Contribution of Learning Outcomes to Programme Outcomes   * Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High 



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