COURSE UNIT TITLE

: STATISTICAL METHODS AND APPLICATIONS OF STATISTIC

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EBE 5503 STATISTICAL METHODS AND APPLICATIONS OF STATISTIC ELECTIVE 3 0 0 5

Offered By

Institute Of Education Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

Offered to

Curriculum and Instruction Non-Thesis (Evening)
Family Education and Counselling Non-Thesis (Evening)
Curriculum and Instruction Non-Thesis

Course Objective

Explain the statistical methods and use these methods.

Learning Outcomes of the Course Unit

1   Define the importance of statistics in research .
2   Define the necessity of the appropriate use of statistical applications in research.
3   List the basic terms related with statistics .
4   Apply the analysis related with descriptive statistics that can be necessary to solve the research problem .
5   Apply the simple correlation and regression analysis.
6   Explain and apply how and with which techniques to analyze the data .
7   Interpret the data obtained through statistical analysis.
8   Determine how to report an academic study.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 The definitions and the importance of statistics in research
2 The types of variables and the types of scales
3 The universe and sample, parameter and statistics
4 The symbol and some of its statistical features
5 Descriptive and inferential statistics
6 Percents and quartiles
7 The arrangement of the data, to list the data, frequency, graphics
8 Mid-term exam
9 The arrangement of the data, to list the data, frequency, graphics
10 Arithmetic mean and median
11 Mode, mean, median, and the relationship of them with mode
12 Percents and quartiles
13 The criteria for variables, range, the deviation of mean, variance, standard deviation, skewness and kurtosis
14 Standard scores, Simple linear regression
15 Final Exam

Recomended or Required Reading

1. Green, B. S., & Salkind, J. N. (2008). Using SPSS for Windows and Macintosh (5th ed.). New Jersey, Prentice Hall.
2. Köklü ve Büyüköztürk (2000). Sosyal Bilimler Için Istatistiğe Giriş. Ankara: PegemA Yayıncılık.
3. Tabacknick B. & Fidell L. (2001) Using Multivariate Statistics, 4th edn. Allyn and Bacon, Boston.
4. Tavşancıl E (2006). Tutumların Ölçülmesi ve SPSS ile Veri Analizi.Ankara: Nobel Yayınları

Planned Learning Activities and Teaching Methods

Explaining, question-answer, discussion, search

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTEG MIDTERM GRADE
2 FCG FINAL COURSE GRADE
3 FCG FINAL COURSE GRADE MTEG * 0.40 + FCG * 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Dr. Bahar BARAN
Dokuz Eylül Üniversitesi, Bilgisayar ve Öğretim Teknolojileri Eğitimi Bölümü
Hasan Ali Yücel Binası Kat: 3 No: 308
Buca/ Izmir

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 13 3 39
Preparation for midterm exam 1 10 10
Preparation for final exam 1 15 15
Preparing assignments 1 10 10
Preparing presentations 1 15 15
Final 1 1 1
Midterm 1 3 3
TOTAL WORKLOAD (hours) 132

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6
LO.1333333
LO.2333333
LO.3333333
LO.4333333
LO.5333333
LO.6333333
LO.7333333
LO.8333333

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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