ISB334 Statistical Package Programs

6 ECTS - 2-2 Duration (T+A)- 6. Semester- 3 National Credit

Information

Code ISB334
Name Statistical Package Programs
Semester 6. Semester
Duration (T+A) 2-2 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. GÜZİN YÜKSEL


Course Goal

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 Content

Introduction to basic computer skills, Preparation of data, Descriptive Statistics, Correlation, Statistical Tests, ANOVA Analysis, Regression Analysis, Coding survey data, Reliability Analysis

Course Precondition

None

Resources

SPSS paket Programı ile İstatistiksel Veri Analizi Prof. Dr. Hamza Erol, Akademisyen Kitabevi

Notes

Course Notes


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Gains the ability of data analysis knowledge and skills.
LO02 Gains the ability to find solutions to operational working problems.
LO03 Students gain the ability to use SPSS.
LO04 Students use the ability to analyze data with SPSS.
LO05 Apply statistics structures using SPSS in a business environment.
LO06 Uses the skills in problem analysis and problem solving.
LO07 Uses the skills in data handling and manipulation.
LO08 Uses the knowledge by using Mathematica documentation and other sources in the internet.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics
PLO02 Bilgi - Kuramsal, Olgusal Emphasize the importance of Statistics in life 4
PLO03 Bilgi - Kuramsal, Olgusal Define basic principles and concepts in the field of Law and Economics
PLO04 Bilgi - Kuramsal, Olgusal Produce numeric and statistical solutions in order to overcome the problems 4
PLO05 Bilgi - Kuramsal, Olgusal Use proper methods and techniques to gather and/or to arrange the data 5
PLO06 Bilgi - Kuramsal, Olgusal Utilize computer systems and softwares 4
PLO07 Bilgi - Kuramsal, Olgusal Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events 3
PLO08 Bilgi - Kuramsal, Olgusal Apply the statistical analyze methods 5
PLO09 Bilgi - Kuramsal, Olgusal Make statistical inference(estimation, hypothesis tests etc.) 4
PLO10 Bilgi - Kuramsal, Olgusal Generate solutions for the problems in other disciplines by using statistical techniques 3
PLO11 Bilgi - Kuramsal, Olgusal Discover the visual, database and web programming techniques and posses the ability of writing programme
PLO12 Bilgi - Kuramsal, Olgusal Construct a model and analyze it by using statistical packages 5
PLO13 Beceriler - Bilişsel, Uygulamalı Distinguish the difference between the statistical methods 3
PLO14 Beceriler - Bilişsel, Uygulamalı Be aware of the interaction between the disciplines related to statistics 4
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Make oral and visual presentation for the results of statistical methods 3
PLO16 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have capability on effective and productive work in a group and individually 3
PLO17 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği 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 2
PLO18 Yetkinlikler - Öğrenme Yetkinliği Develop scientific and ethical values in the fields of statistics-and scientific data collection 4


Week Plan

Week Topic Preparation Methods
1 Introduction to basic computer skills Reading source books-Application Öğretim Yöntemleri:
Tartışma, Soru-Cevap
2 Introduction to SPSS Program Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
3 Preparation of data Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama, Soru-Cevap
4 Data screening and transformation Reading source books-Application Öğretim Yöntemleri:
Tartışma, Beyin Fırtınası
5 Descriptive Statistics Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
6 Correlation Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama, Örnek Olay
7 Tests for means Reading source books-Application Öğretim Yöntemleri:
Soru-Cevap, Örnek Olay
8 Mid-Term Exam Review the topics discussed in the lecture notes Ölçme Yöntemleri:
Yazılı Sınav
9 Statistical Tests Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama, Örnek Olay
10 ANOVA Analysis Reading source books-Application Öğretim Yöntemleri:
Soru-Cevap, Benzetim
11 ANOVA Analysis II Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama, Proje Temelli Öğrenme
12 Regression Analysis Reading source books-Application Öğretim Yöntemleri:
Beyin Fırtınası, Örnek Olay
13 Regression Analysis II Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama, Benzetim
14 Coding survey data Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama, Deney / Laboratuvar
15 Reliability Analysis Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama, Soru-Cevap, Proje Temelli Öğrenme
16 Term Exams Review the topics discussed in the lecture notes Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Review the topics discussed in the lecture notes Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 4 56
Out of Class Study (Preliminary Work, Practice) 14 4 56
Assesment Related Works
Homeworks, Projects, Others 1 2 2
Mid-term Exams (Written, Oral, etc.) 1 12 12
Final Exam 1 28 28
Total Workload (Hour) 154
Total Workload / 25 (h) 6,16
ECTS 6 ECTS