Dokuz Eylül University Information Package / Courses Catalog

Description of Individual Course Units

Course Unit Code	Course Unit Title	Type Of Course	D	U	L	ECTS
STA 4201	STATISTICAL METHODS	ELECTIVE	4	0	0	7

Offered By

Mathematics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR ÖZLEM EGE ORUÇ

Offered to

Mathematics (Evening)
Mathematics

Course Objective

The main objective of this course is to acquaint students with some basic concepts in statistics. They will be introduced to some elementary statistical methods of analysis of data.

Learning Outcomes of the Course Unit

1	Descriptive statistics, the ability to describe data with graphically and numerically
2	Know when and how to apply basic Statistical Inference ideas, Sampling distributions, including the Central Limit Theorem;
3	Appreciate the relationship between confidence intervals and tests of hypotheses
4	Know to apply Hypothesis Testing about One and Two Population Parameters
5	Know when and how to apply the Chi-Square Statistic to test for goodness of fit and for independence
6	Know when and how to apply basic Nonparametric Statistical Tests (Mann-Whitney, Wilcoxon, Spearman's Rank Correlation)
7	Know to apply Analysis of Variance
8	Know how to fit, check and use Simple Linear Regression models

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week	Subject	Description
1	Descriptive Statistic, Data, Data Types
2	DescribingData Graphically(Pie chart, bart chart, steam and life diagram, box plot, histogram etc)
3	Describing Data Numerically(Measure of central tendencey and Measure of variability)
4	Statistical Inference and Sampling Distributions (Z, Chi-square, t, F), Central Limit theorem
5	Point Estimation
6	Inferences Based on a Single Sample: Confidence Interval and Hypotheses Testing
7	Inferences Based on Two Samples: Confidence Interval and Hypotheses Testing
8	Power of test
9	Mid-term Exam
10	Applications of chi-squared Statistic.
11	Analysis of Variance: Comparing More Than Two Means Introduction to Simple Linear Regression
12	Simple Linear Regression
13	Multiple Regression
14	Nonparametric Statistics

Recomended or Required Reading

Textbook(s):
1)Richard J. Larsen (Author), Morris L. Marx ,Introduction to Mathematical Statistics and Its Applications (4th Edition)

2)James T. McClave , Feank H. Dietrich,II, and Terry Sincich, Statistics 13th Edition, Prentice Hall

Planned Learning Activities and Teaching Methods

The course consists of lecture and class discussion

Assessment Methods

SORTING NUMBER	SHORT CODE	LONG CODE	FORMULA
1	MTE	MIDTERM EXAM
2	QUZ	QUIZ
3	ASG	ASSIGNMENT
4	FIN	FINAL EXAM
5	FCGR	FINAL COURSE GRADE (RESIT)	MTE* 0.30 + QUZ * 0.20 + ASG * 0.10 + FIN * 0.40
6	RST	RESIT
7	FCGR	FINAL COURSE GRADE (RESIT)	MTE * 0.30 + QUZ * 0.20 + ASG * 0.10 + RST * 0.40

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

Further Notes About Assessment Methods

None

Assessment Criteria

%30( midterm )+%20(quiz)+%10( homework)+%40( Final exam )

Language of Instruction

English

Course Policies and Rules

Student responsibilities :
Reading the related parts of the course material each week, attending the course and participating in class discussions are the requirements of the course. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at www.fef.deu.edu.tr

Contact Details for the Lecturer(s)

Prof.Dr.Özlem EGE ORUÇ
DEU. Faculty Sciences Department of Statistics B113
e-mail: ozlem.ege@deu.edu.tr
Tel: 0232 3018558

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Lectures	14	4	56
Preparations before/after weekly lectures	14	2	28
Preparation for midterm exam	1	20	20
Preparation for final exam	1	30	30
Preparing assignments	1	14	14
Preparation for quiz etc.	1	15	15
Final	1	2	2
Midterm	1	2	2
Quiz etc.	1	1	1
Project Assignment	1	1	1
TOTAL WORKLOAD (hours)			169

Contribution of Learning Outcomes to Programme Outcomes

PO/LO	PO.1	PO.2	PO.3	PO.4	PO.5	PO.6	PO.7	PO.8	PO.9	PO.10	PO.11	PO.12	PO.13
LO.1	5		4										5
LO.2	5		4										5
LO.3	5		4										5
LO.4	5		4										5
LO.5	5		4										5
LO.6	5		4										5
LO.7	5		4										5
LO.8	5	5	5	5	5	5	5	5	5	5	5	5	5

COURSE UNIT TITLE

DEGREE PROGRAMMES

Description of Individual Course Units

Offered By

Level of Course Unit

Course Coordinator

Offered to

Course Objective

Learning Outcomes of the Course Unit

Mode of Delivery

Prerequisites and Co-requisites

Recomended Optional Programme Components

Course Contents

Recomended or Required Reading

Planned Learning Activities and Teaching Methods

Assessment Methods

Further Notes About Assessment Methods

Assessment Criteria

Language of Instruction

Course Policies and Rules

Contact Details for the Lecturer(s)

Office Hours

Work Placement(s)

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes

CONTACT INFORMATION