COURSE UNIT TITLE

: STATISTICAL METHODS

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   Understand and apply the basic concepts of point, interval estimation, and hypothesis testing
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 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)
4 Describing Data Numerically(Measure of variability)
5 Statistical Inference and Sampling Distributions (Z, Chi-square, t, F), Central Limit theorem
6 Point Estimation
7 Inferences Based on a Single Sample: Confidence Interval
8 Inferences Based on a Single Sample: Hypotheses Testing
9 Basic concepts of Hypothesis Testing
10 Power of test
11 Inferences Based on Two Samples: Confidence Interval
12 Inferences Based on Two Samples:Hypotheses Testing
13 Applications of chi-squared Statistic.
14 Simple Linear Regression

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 VZ Vize
2 FN Final
3 BNS BNS VZ * 0.40 + FN * 0.60
4 BUT Bütünleme Notu
5 BBN Bütünleme Sonu Başarı Notu VZ * 0.40 + BUT * 0.60


Further Notes About Assessment Methods

None

Assessment Criteria

%40( midterm )+%60( 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 4 56
Preparation for midterm exam 1 21 21
Preparation for final exam 1 32 32
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 169

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13
LO.1545
LO.2545
LO.3545
LO.4545
LO.5545
LO.6545