Ders Planı

CLASS 3

Lesson plan / MULTIVARIATE STATISTICS-II

Lesson Information

Course Credit	3.0
Course ECTS Credit	5.0
Teaching Language of Instruction	Türkçe
Level of Course	Bachelor's Degree, TYYÇ: Level 6, EQF-LLL: Level 6, QF-EHEA: First Cycle
Type of Course	Compulsory
Mode of Delivery	Face-to-face
Does the course require compulsory or optional work experience?	Z
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Purpose and Content

The aim of the course	Multivariate statistical methods, the basic definitions, concepts and theorems are given. Variables methods to analyze much of the data.  Multivariate Data, Complex Event, basic definitions, measurements on several different variables (observations) collection techniques
Course Content	Expression vector of multivariate data, the sample mean vector and sample covariance matrix, multivariate distributions, multivariate normal distribution, other multivariate distributions, parametric estimation, hypothesis testing, regression analysis and multivariate methods of dimensionality reduction applies. Multivariate analysis of variance (MANOVA), multivariate significance tests apply more complex experimental designs. Implements multiple independent variables of the univariate ANOVA.

The aim of the course

Multivariate statistical methods, the basic definitions, concepts and theorems are given. Variables methods to analyze much of the data.  Multivariate Data, Complex Event, basic definitions, measurements on several different variables (observations) collection techniques

Course Content

Expression vector of multivariate data, the sample mean vector and sample covariance matrix, multivariate distributions, multivariate normal distribution, other multivariate distributions, parametric estimation, hypothesis testing, regression analysis and multivariate methods of dimensionality reduction applies. Multivariate analysis of variance (MANOVA), multivariate significance tests apply more complex experimental designs. Implements multiple independent variables of the univariate ANOVA.

Learning Outcomes

Has theoretical knowledge in the field of statistics.
Has the ability to use the theoretical resources required for statistics
Has the ability to use the theoretical resources required for statistics
To be able to use the necessary theoretical content resources for statistics
Defines the studies related to statistics independently and with the partners
Describe the current problems with statistical methods
Defines the ability of abstract and analytical thinking
Comprehend the knowledge of computer software and programming technique to be able to apply the science of statistics effectively.
Analyze the theoretical knowledge in probability and statistics
Evaluate different databases as required
Evaluates the outputs of applied questionnaires
Applies the concepts and thoughts in the field with scientific methods
Arrange the data related to the field
Solve the identified statistical problems
Prepares surveys
Develops solutions based on identified statistical problems, evidence and research
Contributes to the professional development of the employees under their management
Define new topics related to statistics
Give lectures and seminars about statistics and probability
Determines the needs for learning
Develops original attitudes towards lifelong learning by guiding learning processes related to learning
He/She organizes projects and activities for the social environment in which he/she lives with an awareness of social responsibility
Students will be able to communicate their solutions to problems related to statistics in written and oral forms
Supports suggestions for solutions and thoughts with quantative and quantative data
Follow developments in the field by using a foreign language
Uses computer software and information-communication-network technologies at the level required by the science of statistics
Students will have social, scientific and ethical values in the publication of the data related to the fields of science
Quality management and process, environmental protection, occupational health and safety issues has sufficient awareness
Gain social, scientific and ethical values in the stages of collecting, interpreting and announcing the data related to the fields of science
Has knowledge about the legal consequences of statistical applications

Weekly Course Subjects

1	None Installed Files multivariate data matrix input and six Multivariate Normal Distribution
2	Graphics
3	Measures of central tendency
4	Variance Covariance and Correlation Matrices
5	Multivariate Normal Distribution
6	Multivariate Normal Distribution
7	Hypothesis Testing
8	Hypothesis Testing
9	Hypothesis Testing
10	Parametric estimation
11	Parametric estimation
12	MANOVA
13	Computer applications in multivariate statistics
14	Computer applications of multivariate statistics

Resources

1-Johnson, Wichern,"Applied Multivariate Statistical Analysis", Prentice Hall, 1998

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Lesson Information

Purpose and Content

Learning Outcomes

Weekly Course Subjects

Resources

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