Course Details

STATISTICS

IE222

Return to Classes
Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
4IE222STATISTICS4+0+046

Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program INDUSTRIAL ENGINEERING
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course To introduce the role of statistics in research and engineering practice.
To develop skills in data gathering and analysis.
To provide tools to interpret experimental results.
To provide sufficient background to support further studies in industrial engineering.
Course Content This course introduces summarizing data and using data to make numerical conjectures to students. The focus is on a broad treatment of applications of statistics, concentrating on techniques used in industry and science. Topics include descriptive statistics, parameter estimation, confidence intervals, hypothesis testing, analysis of variance, and linear regression. The course includes computer implementations using available up-to-date statistical software.
Course Methods and Techniques In class lectures and Tutorials.
Prerequisites and co-requisities ( IE221 )
Course Coordinator None
Name of Lecturers Asist Prof.Dr. Uğur Satıç yok ugur.satic@agu.edu.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Montgomery, Douglas C., and Runger, George C. Applied Statistics and Probability for Engineers. Wiley, 2013.
Tutorial questions from Canvas.
Lecture notes (Available in Canvas)
Montgomery, Douglas C., and Runger, George C. Applied Statistics and Probability for Engineers. Wiley, 2013.
canvas
canvas
canvas

Course Category
Field %100

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı 1 % 30
Yarıl yılSonu Sınavı/Dönem Projesinin Başarı Notuna Katkısı 1 % 5
Ödev 10 % 10
Sunum/Seminer 1 % 5
Final examination 1 % 30
Diğer (Staj vb.) 1 % 20
Total
15
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Soru Çözümü 14 2 28
Proje 1 10 10
Ders dışı çalışma 14 2 28
Yüz Yüze Ders 14 4 56
Ders Dışı Ara Sınav 1 20 20
Final Sınavı 1 25 25
Total Work Load   Number of ECTS Credits 6 167

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Demonstrate understanding of descriptive statistics by summarizing data numerically and graphically.
2 Formulate point estimates and confidence intervals for unknown parameters of distributions.
3 Perform hypotheses testing with one or two samples.
4 Develop linear regression models.
5 Be able to use a statistical software. (R and Excel)
6 Be able to work in a team and share the results of a statistical analysis (written and orally) with peers in a meaningful and professional manner.


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Descriptive Statistics with graphics Skim the section and bring a question so we can solve it in class together. Ders kitabının 6. bölümü
2 Point Estimation of Parameters and Sampling Distributions Skim the section and bring a question so we can solve it in class together. Section 7 of Applied Statistics and Probability for Engineers
3 Statistical Intervals for a Single Sample Skim the section and bring a question so we can solve it in class together Section 8 of Applied Statistics and Probability for Engineers
4 Statistical Intervals for a Single Sample (part 2) Skim the section and bring a question so we can solve it in class together Section 8 of Applied Statistics and Probability for Engineers
5 Statistical Inference for Two Samples Skim the section and bring a question so we can solve it in class together Section 10 of Applied Statistics and Probability for Engineers
6 Statistical Inference for Two Samples (part 2) Skim the section and bring a question so we can solve it in class together Section 10 of Applied Statistics and Probability for Engineers
7 Midterm Exam Check shared questions. Tutorial sets
8 Active Learning Week: Explanation of the course project and investigation of old term projects conducted in previous semesters.
9 Tests of Hypotheses for a Single Sample Skim the section and bring a question so we can solve it in class together Section 9 of Applied Statistics and Probability for Engineers
10 Tests of Hypotheses for Two Samples Skim the section and bring a question so we can solve it in class together Section 10 of Applied Statistics and Probability for Engineers
11 Simple Linear Regression and Correlation Skim the section and bring a question so we can solve it in class together Section 11 of Applied Statistics and Probability for Engineers
12 Multiple Linear Regression (part 1) Skim the section and bring a question so we can solve it in class together Section 12 of Applied Statistics and Probability for Engineers
13 Multiple Linear Regression (part 2) Skim the section and bring a question so we can solve it in class together Section 12 of Applied Statistics and Probability for Engineers
14 Term Project presentations.


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
C1 5
C2 5
C3 5
C4 5
C5 3
C6 3 5 2 3

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant


https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=71658&lang=en
Return to Classes