|Structure Type:||Study unit|
|Type:||Compulsory / Basic Studies|
|Level:||Bachelor of Engineering|
|Year of Study:||3 (2021-2022)|
|Responsible Teacher:||Niemelä, Riitta|
|Language of Instruction:||Finnish|
Courses During the Academic Year 2021-2022
|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|
Still need to take the course? See the courses during the academic year 2022-2023.
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.
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.
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
Mode of Delivery / Planned Learning Activities and Teaching Methods
Contact studies, virtual lectures and exercises, project work.
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.
Examination, project work and exercises. Numeric scale (0-5).