Advanced Mathematical Methods in Economics and ManagementLaajuus (5 cr)
Code: TZ1BA01
Credits
5 op
Objective
The student
-is able to use methods of statistical analysis in applications relating to economics and management, and also use them in real estate management
-can apply probability distributions in reliability engineering
-understands the principles of optimization and regression, and has basic knowledge of most common optimization algorithms
-is able to build simple decision models and knows how to assess risk and uncertainty in modeling
Content
Revision on basics concepts of probability.
Reliability analysis.
Sampling and estimation.
Statistical hypothesis testing.
Optimization and regression.
Decision modeling.
Use of spreadsheet software in applications relating to the topics of the course.
Prerequisites
English level 2.
Assessment criteria, satisfactory (1)
The student
-can apply methods of probability and statistics in simple problems
-shows understanding of basic concepts of reliability engineering and can use them in applications
-is able to use simple linear regression in applications and understands the basic ideas of it
-knows the basics of decision modeling
Assessment criteria, good (3)
In addition of the criteria mentioned above, the student
-has some ability to assess the suitability of different probability distributions and methods of statistical analysis in practical problems
-knows and is able to solve various problems relating to regression analysis and optimization
-can design and build simple decision models
-have understanding about possibilities but also about weaknesses and limitations of the methods studied on the course
-can explain and report her/his solutions clearly
Assessment criteria, excellent (5)
In addition of the criteria mentioned above, the student
-can apply the concepts and methods studied on the course also in more complicated problems
-understands the theoretical background of the concepts and methods, and is able to use that knowledge to assess thoroughly the suitability of them to various practical problems
-can explain and report his/her solutions elaborately
Assessment criteria, approved/failed
The student
-can apply methods of probability and statistics in simple problems
-shows understanding of basic concepts of reliability engineering and can use them in applications
-is able to use simple linear regression in applications and understands the basic ideas of it
-knows the basics of decision modeling
Further information
Virtual course
Enrollment
06.05.2024 - 13.09.2024
Timing
02.09.2024 - 20.12.2024
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
School of Real Estate and Construction
Campus
Myllypurontie 1
Teaching languages
- English
Degree programmes
- Master's Degree Programme in Construction and Real Estate Management.
Teachers
- Ari Koistinen
Teacher in charge
Hannu Hakkarainen
Groups
-
T1724S6Master's Degree Programme in Construction and Real Estate Management, ylempi
Objective
The student
-is able to use methods of statistical analysis in applications relating to economics and management, and also use them in real estate management
-can apply probability distributions in reliability engineering
-understands the principles of optimization and regression, and has basic knowledge of most common optimization algorithms
-is able to build simple decision models and knows how to assess risk and uncertainty in modeling
Content
Revision on basics concepts of probability.
Reliability analysis.
Sampling and estimation.
Statistical hypothesis testing.
Optimization and regression.
Decision modeling.
Use of spreadsheet software in applications relating to the topics of the course.
Evaluation scale
0-5
Assessment criteria, satisfactory (1)
The student
-can apply methods of probability and statistics in simple problems
-shows understanding of basic concepts of reliability engineering and can use them in applications
-is able to use simple linear regression in applications and understands the basic ideas of it
-knows the basics of decision modeling
Assessment criteria, good (3)
In addition of the criteria mentioned above, the student
-has some ability to assess the suitability of different probability distributions and methods of statistical analysis in practical problems
-knows and is able to solve various problems relating to regression analysis and optimization
-can design and build simple decision models
-have understanding about possibilities but also about weaknesses and limitations of the methods studied on the course
-can explain and report her/his solutions clearly
Assessment criteria, excellent (5)
In addition of the criteria mentioned above, the student
-can apply the concepts and methods studied on the course also in more complicated problems
-understands the theoretical background of the concepts and methods, and is able to use that knowledge to assess thoroughly the suitability of them to various practical problems
-can explain and report his/her solutions elaborately
Assessment criteria, approved/failed
The student
-can apply methods of probability and statistics in simple problems
-shows understanding of basic concepts of reliability engineering and can use them in applications
-is able to use simple linear regression in applications and understands the basic ideas of it
-knows the basics of decision modeling
Prerequisites
English level 2.
Further information
Virtual course
Enrollment
29.08.2023 - 08.09.2023
Timing
01.08.2023 - 31.12.2023
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
School of Real Estate and Construction
Campus
Myllypurontie 1
Teaching languages
- English
Degree programmes
- Master's Degree Programme in Construction and Real Estate Management.
Teachers
- Ari Koistinen
Teacher in charge
Hannu Hakkarainen
Groups
-
T1723S6Master's Degree Programme in Construction and Real Estate Management, ylempi
Objective
The student
-is able to use methods of statistical analysis in applications relating to economics and management, and also use them in real estate management
-can apply probability distributions in reliability engineering
-understands the principles of optimization and regression, and has basic knowledge of most common optimization algorithms
-is able to build simple decision models and knows how to assess risk and uncertainty in modeling
Content
Revision on basics concepts of probability.
Reliability analysis.
Sampling and estimation.
Statistical hypothesis testing.
Optimization and regression.
Decision modeling.
Use of spreadsheet software in applications relating to the topics of the course.
Evaluation scale
0-5
Assessment criteria, satisfactory (1)
The student
-can apply methods of probability and statistics in simple problems
-shows understanding of basic concepts of reliability engineering and can use them in applications
-is able to use simple linear regression in applications and understands the basic ideas of it
-knows the basics of decision modeling
Assessment criteria, good (3)
In addition of the criteria mentioned above, the student
-has some ability to assess the suitability of different probability distributions and methods of statistical analysis in practical problems
-knows and is able to solve various problems relating to regression analysis and optimization
-can design and build simple decision models
-have understanding about possibilities but also about weaknesses and limitations of the methods studied on the course
-can explain and report her/his solutions clearly
Assessment criteria, excellent (5)
In addition of the criteria mentioned above, the student
-can apply the concepts and methods studied on the course also in more complicated problems
-understands the theoretical background of the concepts and methods, and is able to use that knowledge to assess thoroughly the suitability of them to various practical problems
-can explain and report his/her solutions elaborately
Assessment criteria, approved/failed
The student
-can apply methods of probability and statistics in simple problems
-shows understanding of basic concepts of reliability engineering and can use them in applications
-is able to use simple linear regression in applications and understands the basic ideas of it
-knows the basics of decision modeling
Prerequisites
English level 2.
Further information
Virtual course
Enrollment
02.07.2023 - 31.07.2023
Timing
01.08.2022 - 31.12.2022
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
School of Real Estate and Construction
Campus
Myllypurontie 1
Teaching languages
- English
Degree programmes
- Master's Degree Programme in Construction and Real Estate Management.
Teachers
- Ari Koistinen
Teacher in charge
Hannu Hakkarainen
Groups
-
T1722S6Master's Degree Programme in Construction and Real Estate Management, ylempi
Objective
The student
-is able to use methods of statistical analysis in applications relating to economics and management, and also use them in real estate management
-can apply probability distributions in reliability engineering
-understands the principles of optimization and regression, and has basic knowledge of most common optimization algorithms
-is able to build simple decision models and knows how to assess risk and uncertainty in modeling
Content
Revision on basics concepts of probability.
Reliability analysis.
Sampling and estimation.
Statistical hypothesis testing.
Optimization and regression.
Decision modeling.
Use of spreadsheet software in applications relating to the topics of the course.
Evaluation scale
0-5
Assessment criteria, satisfactory (1)
The student
-can apply methods of probability and statistics in simple problems
-shows understanding of basic concepts of reliability engineering and can use them in applications
-is able to use simple linear regression in applications and understands the basic ideas of it
-knows the basics of decision modeling
Assessment criteria, good (3)
In addition of the criteria mentioned above, the student
-has some ability to assess the suitability of different probability distributions and methods of statistical analysis in practical problems
-knows and is able to solve various problems relating to regression analysis and optimization
-can design and build simple decision models
-have understanding about possibilities but also about weaknesses and limitations of the methods studied on the course
-can explain and report her/his solutions clearly
Assessment criteria, excellent (5)
In addition of the criteria mentioned above, the student
-can apply the concepts and methods studied on the course also in more complicated problems
-understands the theoretical background of the concepts and methods, and is able to use that knowledge to assess thoroughly the suitability of them to various practical problems
-can explain and report his/her solutions elaborately
Assessment criteria, approved/failed
The student
-can apply methods of probability and statistics in simple problems
-shows understanding of basic concepts of reliability engineering and can use them in applications
-is able to use simple linear regression in applications and understands the basic ideas of it
-knows the basics of decision modeling
Prerequisites
English level 2.
Further information
Virtual course