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Curricular information is subject to change
Statistical Analysis for Research has 5 learning outcomes:
1. Use statistics to reduce complex data situations to manageable formats in order to describe, explain or model them;
2. Derive descriptive statistics for various data types;
3. Perform and critique statistical tests on two sample data;
4. Set up and critically analyse data sets in both a parametric and non-parametric way for two and more samples;
5. Communicate effectively research findings in a clear concise manner using correct terminology using SPSS.
This statistic course is delivered over 3 days and works from an Introduction to data analysis through statistical Inference with SPSS, multi-variable data analysis and then correlation and multiple regression.
The course includes worked examples and illustrations culminating in an MCQ.
This module is useful for researchers at a stage in their research when they have a set of data.
Student Effort Type | Hours |
---|---|
Lectures | 21 |
Specified Learning Activities | 28 |
Autonomous Student Learning | 51 |
Total | 100 |
Not applicable to this module.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Multiple Choice Questionnaire: At the end of the module an MCQ is conducted to assess the acquired knowledge and skill | End of trimester MCQ | n/a | Pass/Fail Grade Scale | Yes | 100 |
Resit In | Terminal Exam |
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Summer | No |
• Feedback individually to students, post-assessment
Not yet recorded.
Name | Role |
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Mr SEAN LACEY | Tutor |