Elementary Statistics (STAT211) Course Detail

Course Name	Course Code	Season	Lecture Hours	Application Hours	Lab Hours	Credit	ECTS
Elementary Statistics	STAT211	Diğer Bölümlere Verilen Ders	3	0	0	3	5

Pre-requisite Course(s)
None

Course Language	English
Course Type	Service Courses Given to Other Departments
Course Level	Bachelor’s Degree (First Cycle)
Mode of Delivery	Face To Face
Learning and Teaching Strategies	Lecture, Question and Answer, Problem Solving.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives	In addition to some classification and summarization tools, such as tables, graphs and central tendency and dispersion measures to process raw data, to provide students with basic probability knowledge and showing wide range of applications of statistics in social sciences
Course Learning Outcomes	The students who succeeded in this course; After successful completion of the course the students will: 1- know how to organize a set of data in an informative way; 2- understand what measures of central tendency and dispersion of the data are be able to calculate, interpret them, 3- understand the basic concept of probability including some counting techniques, 4- have ability to calculate the classical and conditional probability,have knowledge on statistically independency; 5- understand the difference between discrete and continuous random variables; know properties and possess skill to apply binomial distribution and normal distribution to various practical problems.
Course Content	Descriptive Statistics such as mean, median mode and standard deviation, The Notion of Probability, Random Event/ Experiment, Conditional Probability, Statistical Independency, Random Variables, Probability Distribution Table, Binomial Distribution and Normal Distribution.

Weekly Subjects and Releated Preparation Studies

Week	Subjects	Preparation
1	Basic Definitions, Frequency Distributions	pp. 4 – 17, 51-59
2	Graphic Presentation of Data, Stem-and-Leaf Display	pp:. 59-72
3	Central Tendency Measures; Mean, Median and Mode for Ungrouped and Grouped Data	pp. 73-86
4	Measures of Dispersion: Variance, Standard Deviation, Coefficient of Variation	pp. 88-111
5	Random Event, Random Experiment, Sample Space, Meaning of Probability	pp. 127-132
6	Classical / Postrerior Probability Definitions, Multiplication Rule	pp. 150- 160
7	Midterm Exam
8	Venn Diagrams, Contingency Table	pp. 137-140
9	Conditional Probability, Statistical Independency	pp. 140-146
10	Meaning of Random Variable, Examples in Daily Life, Probability Distribution Table	pp. 147-151
11	Expected Value , Mean and Standard Deviation of a Random Variable	pp. 152-157
12	Binomial Distribution and how to use for Probability	pp. 167-176
13	Normal Distribution and Applications in Various Scientific Area and Daily Life	pp. 182-184
14	Standard Normal Table ( Z table ) and how to use in problems	pp. 184-195
15	Review
16	Final Exam

Sources

Course Book	1. D.H. Sanders, R. K. Smidt, Statistics, A First Course, 1990
Other Sources	2. A. G. Bluman, Elementary Statistics, A step by step Approach, McGrawHill 2001

Evaluation System

Requirements	Number	Percentage of Grade
Attendance/Participation	-	-
Laboratory	-	-
Application	-	-
Field Work	-	-
Special Course Internship	-	-
Quizzes/Studio Critics	-	-
Homework Assignments	2	10
Presentation	-	-
Project	-	-
Report	-	-
Seminar	-	-
Midterms Exams/Midterms Jury	2	50
Final Exam/Final Jury	1	40
Toplam	5	100

Percentage of Semester Work	60
Percentage of Final Work	40
Total	100

Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

#	Program Qualifications / Competencies	Level of Contribution
#	Program Qualifications / Competencies	1	2	3	4	5
1	Acquires skills to use the advanced theoretical and applied knowledge obtained at the mathematics bachelors program to do further academic and scientific research in both mathematics-based graduate programs and public or private sectors.
2	Transplants and applies the theoretical and applicable knowledge gained in their field to the secondary education by using suitable tools and devices.
3	Acquires the skill of choosing, using and improving problem solving techniques which are needed for modeling and solving current problems in mathematics or related fields by using the obtained knowledge and skills.
4	Acquires analytical thinking and uses time effectively in the process of deduction
5	Acquires basic software knowledge necessary to work in the computer science related fields and together with the skills to use information technologies effectively.
6	Obtains the ability to collect data, to analyze, interpret and use statistical methods necessary in decision making processes.
7	Acquires the level of knowledge to be able to work in the mathematics and related fields and keeps professional knowledge and skills up-to-date with awareness in the importance of lifelong learning.
8	Takes responsibility in mathematics related areas and has the ability to work affectively either individually or as a member of a team.
9	Has proficiency in English language and has the ability to communicate with colleagues and to follow the innovations in mathematics and related fields.
10	Has the ability to communicate ideas with peers supported by qualitative and quantitative data.
11	Has professional and ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications.

ECTS/Workload Table

Activities	Number	Duration (Hours)	Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class	16	3	48
Presentation/Seminar Prepration
Project
Report
Homework Assignments	2	3	6
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury	2	15	30
Prepration of Final Exams/Final Jury
Total Workload			84