Statistical Mathematics
| Structure Type: | Study unit |
|---|---|
| Code: | TLVP1502 |
| Type: | Compulsory / Basic Studies |
| Curriculum: | EY 2015V / 2017V / 2018V I-RT 2013V KT 2014V / 2016V / 2018V / 2019V LT 2014V / 2015V / 2016V / 2017V / 2018V / 2019V / 2020V RT 2015V ST 2014V / 2016V / 2018V / 2020V T-LT 2013V TT 2014V / 2016V / 2018V / 2020V |
| Level: | Bachelor of Engineering / Bachelor of Business Administration |
| Year of Study: | 3 / 4 (2015-2016 / 2016-2017 / 2017-2018 / 2018-2019 / 2019-2020 / 2020-2021 / 2021-2022 / 2022-2023) |
| Credits: | 2 cr |
| Responsible Teacher: | Niemelä, Riitta / Laaja, Martti / Niittykoski, Jukka / Mäkinen, Seppo |
| Language of Instruction: | Finnish |
Courses
| Impl. | Group(s) | Study Time | Teacher(s) | Language | Enrolment |
|---|---|---|---|---|---|
| 1 | H-VV | 2015-09-10 – 2016-05-31 | Mikko Ranta | Finnish | 2015-09-09 – 2016-05-30 |
| 2 | 2016-01-04 – 2016-05-31 | Mikko Ranta | Finnish | 2015-12-07 – 2016-01-10 | |
| 3 | I-RT-3V | 2016-01-04 – 2016-05-21 | Mikko Ranta | Finnish | 2015-12-07 – 2016-01-10 |
| 4 | 2017-01-09 – 2017-04-29 | Kerstin Siegfrids | Finnish | 2016-12-12 – 2017-01-16 | |
| 5 | I-ST-3V, I-TT-3V | 2017-03-06 – 2017-05-30 | Mikko Ranta | Finnish | 2016-12-12 – 2017-01-16 |
| 6 | 2017-09-01 – 2017-12-22 | Kerstin Siegfrids | Finnish | 2017-08-21 – 2017-09-18 | |
| 7 | I-EY-3V, I-RT-3V | 2017-08-25 – 2017-12-22 | Mikko Ranta | Finnish | 2017-08-21 – 2017-09-18 |
| 8 | I-KT-2V, I-TT-2V | 2018-01-08 – 2018-05-26 | Jussi Ojanen | Finnish | 2017-12-11 – 2018-01-15 |
| 10 | T-LT-4VT | 2018-08-31 – 2018-12-21 | Kerstin Siegfrids | Finnish | 2018-08-20 – 2018-09-17 |
| 11 | I-ST-3V | 2019-01-07 – 2019-05-18 | Jussi Ojanen | Finnish | 2018-12-10 – 2019-01-14 |
| 12 | T-LT-3VK | 2019-09-02 – 2019-12-22 | Kerstin Siegfrids | Finnish | 2019-08-19 – 2019-09-09 |
| 13 | I-EY-3V | 2019-10-21 – 2019-12-20 | Jarmo Mäkelä | Finnish | 2019-08-19 – 2019-09-09 |
| 14 | I-ST-2V | 2019-10-21 – 2020-02-21 | Jussi Ojanen | Finnish | 2019-08-19 – 2019-09-09 |
| 3001 | EY2018V-3, EY2018V-3A, KT2018V-3, KT2018V-3A, KT2018V-3B | 2021-01-04 – 2021-05-02 | Onni Pyhälahti | Finnish | 2020-08-17 – 2021-01-10 |
| 3002 | LT2018V-3T | 2021-01-04 – 2021-02-28 | Kerstin Siegfrids | Finnish | 2020-08-17 – 2021-01-10 |
| 3003 | TT2018V-3A | 2021-01-04 – 2021-02-28 | Jussi Ojanen | Finnish | 2020-08-17 – 2021-01-10 |
| 3005 | KT2019V-3A, KT2019V-3B | 2021-08-02 – 2021-10-25 | Kerstin Siegfrids, Lotta Saarikoski | Finnish | 2021-08-01 – 2021-09-06 |
| 3006 | LT2019V-3K | 2022-01-03 – 2022-02-27 | Kerstin Siegfrids | Finnish | 2021-12-01 – 2022-01-10 |
| 3007 | ST2020V-2, ST2020V-2A, ST2020V-2B | 2021-10-17 – 2022-02-25 | Jussi Ojanen | Finnish | 2021-08-01 – 2021-09-06 |
| 3010 | TT2020V-3, TT2020V-3A, TT2020V-3B | 2023-03-06 – 2023-05-13 | Kerstin Siegfrids | Finnish | 2022-12-01 – 2023-01-09 |
| 3011 | LT2020V-3T | 2023-01-02 – 2023-03-05 | Kerstin Siegfrids | Finnish | 2022-12-01 – 2023-01-10 |
The descriptions shown below are for the academic year: 2022-2023
Learning Outcomes
The student is able to find statistical data and interpret statistical figures. The student is able to analyze statistical data with different statistics. The student knows the basics of correlation and regression analysis, and is able to run variance analysis and T-test analysis. The student can critically analyze the results acquired from the research. The student is able to use Excel software for statistical analysis.
Student's Workload
54 hours, of which
6 hours of scheduled studies
14 hours of virtual studies, and
34 hours of autonomous studies
The assessment of student’s own learning 1 h is included in contact lessons.
Contents
Basic terms, statistical charts, parameter estimation, linear regression, dependence analysis, correlation, variance, T-test. Using Excel in statistical research.
Recommended or Required Reading and Other Learning Resources/Tools
Lecture notes
Mode of Delivery / Planned Learning Activities and Teaching Methods
Contact studies, virtual lectures and exercises, project work.
Assessment Criteria
1 the student is able to recognise and use the basic concepts of statistical analysis, and can calculate the most common characteristic values of a given material.
3 the student can carry out a statistical analysis on the internal dependences and influences of a given sample of data, e.g., correlations, regression and the T-test.
5 the student can interpret statistical analyses, draw logical conclusions, and apply the obtained knowledge and skills with challenging statistical samples.
Assessment Methods
Examination, project work and exercises. Numeric scale (0-5).