Nursing Research and Development III
Structure Type: | Study unit |
---|---|
Code: | SSHP2003 |
Type: | Compulsory / Basic Studies |
Curriculum: | SH 2015V |
Level: | Bachelor of Health Care |
Year of Study: | 3 (2018) |
Credits: | 2 cr |
Responsible Teacher: | Elomaa, Virpi |
Language of Instruction: | Finnish |
Courses During the Year 2018
Impl. | Group(s) | Study Time | Teacher(s) | Language | Classes | Enrolment |
---|---|---|---|---|---|---|
12 | S-SH-2VK | 2017-09-01 – 2018-04-20 | Paula Hakala | Finnish | 2017-08-21 – 2017-09-18 | |
15 | S-TH-3A | 2017-11-27 – 2018-04-30 | Paula Hakala | Finnish | ||
16 | S-SH-3CK, S-SH-3DK | 2018-01-08 – 2018-06-01 | Paula Hakala | Finnish | 2017-12-11 – 2018-01-15 | |
17 | S-SH-3B | 2018-01-08 – 2018-06-01 | Paula Hakala | Finnish | 2017-12-11 – 2018-01-15 | |
18 | S-SH-3C | 2018-01-08 – 2018-06-01 | Paula Hakala | Finnish | 2017-12-11 – 2018-01-15 | |
19 | S-TH-3A | 2018-01-08 – 2018-06-01 | Paula Hakala | Finnish | 2017-12-11 – 2018-01-15 | |
20 | S-SH-3A | 2018-08-31 – 2018-12-21 | Anne Puska | Finnish | 22 h | 2018-08-20 – 2018-09-17 |
21 | S-SH-3B | 2018-08-31 – 2018-12-21 | Anne Puska | Finnish | 22 h | 2018-08-20 – 2018-09-17 |
22 | S-TH-3A | 2018-08-31 – 2018-12-21 | Anne Puska | Finnish | 22 h | 2018-08-20 – 2018-09-17 |
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.