Nursing Research and Development III
| Structure Type: | Study unit |
|---|---|
| Code: | SSHP2003 |
| Type: | Compulsory / Basic Studies |
| Curriculum: | S-SH 2013VK |
| Level: | Bachelor of Health Care |
| Year of Study: | 3 (2016) |
| Credits: | 2 cr |
| Responsible Teacher: | Elomaa, Virpi |
| Language of Instruction: | Finnish |
Courses During the Year 2016
| Impl. | Group(s) | Study Time | Teacher(s) | Language | Enrolment |
|---|---|---|---|---|---|
| 3 | S-SH-3A | 2016-01-04 – 2016-06-04 | Paula Hakala | Finnish | 2015-12-07 – 2016-02-10 |
| 4 | S-TH-3A, S-TH-3B | 2016-02-22 – 2016-06-04 | Paula Hakala | Finnish | 2015-12-07 – 2016-03-11 |
| 5 | S-SH-3VK | 2016-01-04 – 2016-06-04 | Anne Puska | Finnish | 2015-12-07 – 2016-02-10 |
| 6 | S-TH-3A, S-TH-3B | 2016-08-29 – 2016-12-23 | Paula Hakala | Finnish | 2016-08-22 – 2016-09-19 |
| 7 | S-SH-3B | 2016-08-29 – 2016-12-16 | Paula Hakala | Finnish | 2016-08-22 – 2016-09-19 |
Still need to take the course? See the courses during the academic year 2018-2019.
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 1 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.