At the end of this course, the students; 1) Decide on appropriate basic statistical analysis, 2) Performs calculations and analysis by himself, 3) Comment the results, 4) Comprehends statistical analyzes in the literature in their field, 5) Have sufficient theoretical and practical basis for more advanced statistics courses.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
To teach basic statistical concepts and methods, with examples and applications specific to the field of health, to enable students to understand and evaluate the literature in their field statistically.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Basic statistical concepts; statistics, biostatistics, usage areas of biostatistics, society, sample, statistics, parameters, data, variables, scale types, etc.
2nd Week
Introduction to statistical packages
3rd Week
Classification of data, frequency table generation, etc.
4th Week
Data collection, data collection methods, surveys, etc.
5th Week
data entry application
6th Week
Central tendency and distribution measures; mean, mode, median, standard deviation, variance, standard error, etc.
7th Week
Midterm
8th Week
Calculation of central tendency and dispersion measures.
9th Week
Tables and graphics; table types, chart types, etc.
10th Week
Creating tables, drawing graphs, etc.
11th Week
Single sample t test, independent samples t test, paired t test.
1. Özdamar, K. (2013). SPSS ile Biyoistatistik. Nisan Kitabevi, Eskişehir. 2. Alpar R. (2014). Spor, Sağlık ve Eğitim Bilimlerinden Örneklerle UYGULAMALI İSTATİSTİK ve GEÇERLİK-GÜVENİRLİK. Detay Yayıncılık, Ankara. 3. Daniel Wayne W. and Chad L. Cross. (2013). Biostatistics: A Foundation for Analysis in the Health Sciences. 10th Edition, New York: John Wiley&Sons. 4. Rosner, B. (2015). Fundamentals of biostatistics. Nelson Education.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Lecture,Discussion,Problem Solving
ASSESSMENT METHODS AND CRITERIA
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
1
1
Preparation for Quiz
0
0
0
Individual or group work
14
1
14
Preparation for Final exam
1
10
10
Course hours
14
2
28
Preparation for Midterm exam
1
5
5
Laboratory (including preparation)
0
0
0
Final exam
1
2
2
Homework
0
0
0
Total Workload
60
Total Workload / 30
2
ECTS Credits of the Course
2
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)