Course Title: Analyse data and report results
Part B: Course Detail
Teaching Period: Term2 2012
Course Code: MATH5334C
Course Title: Analyse data and report results
School: 155T Vocational Health and Sciences
Campus: City Campus
Program: C5283 - Diploma of Laboratory Technology (Pathology Testing)
Course Contact: Amberlee Mitton
Course Contact Phone: +61 3 9925 8053
Course Contact Email: amberlee.mitton@rmit.edu.au@rmit.edu.au
Name and Contact Details of All Other Relevant Staff
Namrita Kaul
9925 4309
namrita.kaul@rmit.edu.au
Nominal Hours: 80
Regardless of the mode of delivery, represent a guide to the relative teaching time and student effort required to successfully achieve a particular competency/module. This may include not only scheduled classes or workplace visits but also the amount of effort required to undertake, evaluate and complete all assessment requirements, including any non-classroom activities.
Pre-requisites and Co-requisites
Pre-Requisites MSL924001A - Process and interpret data
Course Description
This unit of competency covers the ability to perform scientific calculations, analyse trends and uncertainty in data and report results within the required timeframe.
National Codes, Titles, Elements and Performance Criteria
National Element Code & Title: |
MSL925001A Analyse data and report results |
Element: |
1. Perform scientific calculations |
Performance Criteria: |
1.1 Ensure raw data are consistent with expectations and reasonable ranges |
Element: |
2. Analyse trends and relationships in data |
Performance Criteria: |
2.1 Determine linear and non-linear relationships between sets of data |
Element: |
3. Determine variation and/or uncertainty in data distributions |
Performance Criteria: |
3.1 Organise raw data into appropriate frequency distributions |
Element: |
4. Check for aberrant results |
Performance Criteria: |
4.1 Identify results that cannot be reconciled with sample, sample documentation, testing procedures and/or expected outcomes |
Element: |
5. Report results |
Performance Criteria: |
5.1 Use charts, tables and graphs to present results in the required format |
Learning Outcomes
Details of Learning Activities
1. Lectures
2. Online learning activites
3. Computer Based tutorials
Teaching Schedule
Week Starting | Week No | Topic | EoC |
9th July | 1 | • Introduction to Statistics • Basic Statistics • Descriptive Statistics |
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16th July |
2 | • Continue with previous week • Equations involving pH, [H], [OH], buffer calculations, Ka, pKa, Kb, pKb, Kw • Henderson – Hasselbach equation |
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23rd July |
3 | • Correlation • Linear and Non-Linear relationship between data |
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30th July |
4 | • Normal Distribution • Control Charts |
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6th August | 5 | • Continue with Control Charts • Types of Control charts |
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13th August | 6 | 1. Normal Distribution 2. z scores calculations |
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20th August | 7 | • Calculating confidence limits for the means • More on Normal Distribution • Revision for mid sem |
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27th August | 8 | Mid semester exams | |
3rd Sept | 9 |
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10h Sept | 10 |
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17th Sept | 11 |
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24th Sept | 12 |
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1st Oct | 13 |
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8th Oct | 14 |
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15th Oct | 15 |
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22nd Oct | 16 | Revision | |
29th Oct | 17 | Exams |
Learning Resources
Prescribed Texts
References
Other Resources
Handouts on MyStudies RMIT
Class room activities
Overview of Assessment
Assessments for this course typically consist of:
• Class activities
• Assignments
• Presentations
• Exams
Assessment Tasks
The following tasks will be conducted during the semester:
- Two assignments (10% each)
- Mid sem exam(30%)
- Minitab exam(10%)
- End of sem exam(40%)
(More details will be provided during the classes)
Assessment Matrix
Course Overview: Access Course Overview