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Week
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Topics
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Study Metarials
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1
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Introduction
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Lecture Note
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2
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Basic Statistics
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Lecture Note
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3
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Basic Statistics
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Lecture Note
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4
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Introduction to Multivariate Data Analysis in Engeineering
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Lecture Note
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5
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Data Modelling Techniques in Engineering
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Lecture Note
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6
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Manipulation of the Data
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Lecture Note
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7
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Factor Analysis in Engineering
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Lecture Note
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8
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Regression Analysis in Engineering
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Lecture Note
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9
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Discriminant Analysis in Engineering
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Lecture Note
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10
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Logistic Regression in Engineering
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Lecture Note
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11
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Cluster Analysis in Engineering
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Lecture Note
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12
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Multivariate Variance Analysis in Engineering
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Lecture Note
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13
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Investigating the problems in Regression
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Lecture Note
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14
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Investigating the problems in Cluster Analysis
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Lecture Note
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Prerequisites
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-
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Language of Instruction
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Turkish
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Responsible
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-
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Instructors
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-
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Assistants
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-
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Resources
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Multivariate Data Analysis ,Joseph F. Hair (Author), William C. Black (Author), Barry J. Babin (Author), Rolph E. Anderson (Author), Pearson Education, 7th Edition, 2009.
Byrne (2009) Structural Equation Modeling With Amos: Basic Concepts, Applications, And Programming, 2nd Edition. Taylor And Francis
Hair, J., F., Anderson, R., E., (2010). Multivariate Data Anlaysis, Lousiana State Universit.
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Supplementary Book
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-
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Goals
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Frequently used analyzes in engineering and basic multivariate data analysis techniques will be explained. The analysis will focus on the selection of the appropriate method, the analysis of the assumptions, the analysis and interpretation of the results.
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Content
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Introduction
Basic statistics
Introduction to multivariate statistics in engineering
Data modeling techniques in engineering
Data manipulation and data adaptation
Factor analysis in engineering
Regression analysis in engineering
Discriminant analysis in engineering
Logistic regression in engineering
Clustering analysis in engineering
Multivariate analysis of variance in engineering (Multiple Anova, MANOVA)
Regression problem solutions
Cluster analysis problem solutions
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Program Learning Outcomes |
Level of Contribution |
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1
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To make scientific researches and reach the knowledge in depth; analyze interpret and apply the knowledge.
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3
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2
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To have knowledge about current technics, methods and their limitations applied in engineering.
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4
|
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3
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To have the ability to define and practice the knowledge by using scientific methods and limited or restricted data and to use the knowledge from other disciplines.
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3
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4
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To have awareness about the new and developing implementations in engineering and to research and learn them when required.
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-
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5
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To define and formulate problems concerning chemical engineering , to develop methods for solution and to apply innovative methods for solutions.
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3
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6
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To develop new and/or original ideas and methods, to design complex systems and processes and to improve alternative/innovative solutions.
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3
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7
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To design and apply theoretical, applied and simulative researches, to analyse and solve complicated problems encountered during these processes.
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3
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8
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To lead in multidisciplinary teams, improve solutions in complex situation and to work independently and take responsibility.
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4
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9
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To use English at least in European Language Portfolio B2 level for both oral and written skills.
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-
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10
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To declare the results and processes of studies both orally and written in national and international platforms with a systematically and concisely manner.
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4
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11
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To have awareness about the social, enviromental, health, security and law perspectives and project management and career applications of engineering practices and restrictions of all these.
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-
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12
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To regard social, scientific liabilities, and ethics during the collection, evaluation, and publication steps of data.
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3
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