LINEAR STATISTICS AND MODELS

SEÇ167

Course Type

Elective Course

Course Level

Associate Degree

Year of Study

Semester

ECTS

Name of Lecturer(s)

Learning Outcomes

At the end of this course, the students;

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

Course Description

This course aims to recall the basic knowledge of probability and statistics and to teach methods of analysis by examining models.

Course Contents

WEEK	TOPICS
1^st Week	Generalized Inverse Matrices
2^nd Week	Distributions and Quadratic Forms
3^rd Week	Introduction of Linear Models
4^th Week	Non-Full Rank Models
5^th Week	Two Parameter Models
6^th Week	1-Factor Classification
7^th Week	2-Factor Cross Classification
8^th Week	Midterm Exam Week
9^th Week	Variance Components
10^th Week	Forecasting in case of Unstable Data
11^th Week	Sum of Squares Sum of Squares
12^th Week	Tests (Ftesti-Square Test)
13^th Week	Some Other Analyzes
14^th Week	Statistical Tables

Recommended or Required Reading

Planned Learning Activities and Teaching Methods

Assessment Methods and Criteria

	Quantity	Percentage (%)
Mid-term	1	40
Total(%)		40
Contribution of In-term Studies to Overall Grade(%)		40
Contribution of Final Examination to Overall Grade(%)		60
Total(%)		100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Midterm exam	1	1	1
Preparation for Quiz
Individual or group work	14	3	42
Preparation for Final exam	14	2	28
Course hours	14	3	42
Preparation for Midterm exam	14	2	28
Laboratory (including preparation)
Final exam	1	1	1
Homework
Total Work Load			142
Total Work Load / 30 (h)			4.73
ECTS Credit of the Course			5

Language of Instruction

Turkish

Work Placement(s)