Nursing Research and Development III
| Structure Type: | Study unit |
|---|---|
| Code: | SSHP2003 |
| Type: | Compulsory / Basic Studies |
| Curriculum: | SH 2017 / 2017V / 2018 TH 2017 |
| Level: | Bachelor of Nursing / Bachelor of Public Health |
| Year of Study: | 3 (2019-2020 / 2020 / 2020-2021) |
| Credits: | 2 cr |
| Responsible Teacher: | Saikkonen, Sanna / Hakala, Paula |
| Language of Instruction: | Finnish |
Courses During the Year 2020
| Impl. | Group(s) | Study Time | Teacher(s) | Language | Enrolment |
|---|---|---|---|---|---|
| 24 | S-SH-2CK, S-SH-2DK | 2020-01-06 – 2020-05-24 | Anne Puska | Finnish | 2019-12-16 – 2020-01-14 |
| 25 | S-SH-2DK | 2020-01-06 – 2020-05-24 | Anne Puska | Finnish | 2019-12-16 – 2020-01-14 |
| 28 | S-SH-2VK | 2020-01-06 – 2020-05-24 | Anne Puska | Finnish | 2019-12-16 – 2020-01-14 |
| 3001 | SH2018-3A | 2020-08-24 – 2020-12-20 | Anne Puska | Finnish | 2020-08-17 – 2020-09-11 |
| 3002 | SH2018-3B | 2020-08-24 – 2020-12-20 | Anne Puska | Finnish | 2020-08-17 – 2020-09-11 |
Learning Outcomes
The student is able to apply the most common statistical data analysis methods
Student's Workload
Total work load of the course: 53 h
- of which scheduled studies: 26 h
- of which autonomous studies: 27 h
The assesment of student's own learning 1 h is included in contact lessons.
Prerequisites / Recommended Optional Courses
Prerequisites: Nursing Research and Development I
Contents
Statistical data analysis methods
Recommended or Required Reading and Other Learning Resources/Tools
Material pointed out by the teacher
Mode of Delivery / Planned Learning Activities and Teaching Methods
Lectures 24 h (including excercises), examination 2 h
Assessment Criteria
Grade 1: The student is able to
- name some of the methods for quantitative data analysis and apply some of them by using tutoring
Grade 3: The student is able to
- describe some of the methods for qualitative and quantitative data analysis and apply some of them
Grade 5: The student is able to
- describe the key methods for quantitative data analysis and apply them
Assessment Methods
Examinations 100%. Numeric grading 0-5.