UC2SAT10 Statistical Analysis: Tools and Techniques
UC2SAT10 Statistical Analysis: Tools and Techniques
- Course description
- NQF LevelBachelor's degree (Level 6 1. Cycle)
- Area of StudyComputing
- Program of StudyApplied Data Science
- ECTS10
- CampusKristiansand, OnlinePLUS - Bergen, OnlinePLUS - Oslo, Online
- Course LeaderIsah Lawal
Language of Instruction and assessment: English
May be offered on Campus and Online.
May be offered as a separate course.
Included in the following bachelor's degrees:
- Applied Data Science
The course aims to introduce the statistical analysis and techniques needed for scientifically analysing and interpreting data. It will cover the fundamentals of statistics through to the development and testing of hypotheses. By the end of this course students will be able to perform a range of statistical analysis to a variety of datasets in order to derive appropriate conclusions from the data.
The student has knowledge of
| K1 | the difference between variety of types of data. |
|---|---|
| K2 | how to apply a variety of statistical techniques for analysing data within scientific research. |
| K3 | legal and ethical issues relating to the statistical analysis of data and presentation of results. |
The student gain skills in
| S1 | development and testing of hypotheses. |
|---|---|
| S2 | ability to select, apply and critically evaluate a variety of statistical tests. |
| S3 | undertaking statistical analysis on a variety of data sets using appropriate statistics software tools. |
| S4 | interpret results of the application of statistical tools and methods to data sets. |
| S5 | consideration of stakeholder requirements in the interpretation and presentation of results. |
The student can demonstrate
| G1 | understanding and explaining the limitations of statistical data analysis and various data collection and analysis techniques. |
|---|---|
| G2 | identifying and managing complex ethical issues relating to the statistical analysis of data, and the use of derived results. |
| G3 | designing and successfully implementing statistical analysis projects with the use of appropriate tools and technologies, whilst considering relevant ethical requirements and principles. |
| G4 | critically reflecting upon the results of statistical analysis. |
| G5 | understand, and be able to inform others, about the kinds of data-driven problematic situations within which statistical concepts and techniques can be appropriately utilised. |
- Introduction to Statistics
- Hypothesis Testing
- Descriptive Statistics
- Significance
- Statistical Tests
- Professionalism in Statistical Analysis
- Statistical Analysis
- Teaching will be based on a hybrid-flexible approach. Instructor-led face-to-face learning is combined with online learning in a flexible course structure that gives students the option of attending sessions in the classroom, participating online, or doing both.
- All activities require active student participation in their own learning.
- Learning delivery methods and available resources will be selected to ensure constructive alignment with course content, learning outcomes and assessment criteria.
- Students will be taught using a mixture of guidance, self-study, and lecture material. Topics will be introduced in a series of weekly lectures. The guidance sessions will be directed practical exercises and reading in which students can explore topics with support from a teacher. This material will also require students to self-manage their time to ensure tasks are completed and the theory is fully understood. This will allow the students to fully engage with lectures and with their peers.
- Learning resources are available in the LMS and include, but is not limited to:
- literature and online reading material (essential and recommended)
- streams, recordings and other digital resources, where applicable
- video conferencing and communication platforms, if applicable
- tools, software and libraries, where applicable
- Students must have access to an internet connection, and suitable hardware.
- Accessing live streams and virtual laboratories requires a minimum broadband connection of 2Mbps (4Mbps recommended).
- Students working on their own laptop/computer are required to acquire appropriate communications software, e.g., webcam, microphone, headphones.
UC1DMA10 Discrete Mathematics, or equivalent course(s).
The reading list for this course and any additional electronic resources will be provided in the LMS.
| Activity | Duration |
|---|---|
Teacher-led activity | 24 |
Teacher-supported work | 48 |
Self-study | 178 |
This course has two (2) exams contributing towards the overall and final grade of the course.
All exams must be assessed as passed to receive the final Course Grade.
| Form of assessment | Grading scale | Grouping | Duration of assessment |
|---|---|---|---|
Portfolio of Work | A-F | ||
Portfolio of Work | A-F |