Course Title: Analyse data and report results
Part B: Course Detail
Teaching Period: Term2 2013
Course Code: MATH5334C
Course Title: Analyse data and report results
School: 155T Vocational Health and Sciences
Campus: City Campus
Program: C5282 - Diploma of Laboratory Technology (Biotechnology)
Course Contact: Amberlee Mitton
Course Contact Phone: +61 3 9925 8053
Course Contact Email: amber.mitton@rmit.edu.au
Name and Contact Details of All Other Relevant Staff
Namrita Kaul
99254309
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
8th July |
• Introduction to Statistics • Basic Statistics • Descriptive Statistics |
|
15th July
|
• Continue with previous week • Equations involving pH, [H], [OH], buffer calculations, Ka, pKa, Kb, pKb, Kw • Henderson – Hasselbach equation |
|
22nd July
|
• Correlation • Linear and Non-Linear relationship between data |
|
29th July
|
• Normal Distribution • Control Charts |
|
5th h August
|
• Continue with Control Charts • Types of Control charts |
|
12th August |
1. Normal Distribution 2. z scores calculations |
|
19th August |
• Calculating confidence limits for the means • More on Normal Distribution • Revision for mid sem |
|
26th August |
Mid semester exams | |
2nd Sept |
• Conducting Statistical Tests • . z-test |
|
9th Sept |
• t-test and using Minitab | |
16th Sept |
• Conducting Chi-square and using Minitab | |
23rd Sept |
• Mid Semester Break | |
30th Sept |
• Conducting ANOVA using Minitab | |
7th Oct |
• Case studies based on all statistical tests | |
14th Oct |
• Continue with previous week. | |
21st Oct |
Revision/ Catch up | |
28th Oct | Exam Week | |
Learning Resources
Prescribed Texts
Handouts and Online Learning materials will be provided during the course. |
References
Practical statistics for the health sciences / Peter Martin, Robyn Pierce |
|
Statistics for starters / Peter Martin & Robyn Pierce |
Other Resources
Handouts on MyStudies RMIT
Overview of Assessment
Assessments for this course typically consist of:
• Class activities
• Assignments
• Presentations
• Exams
Assessment Tasks
To demonstrate competency in this course you need to successfully complete each one of the following pieces of
Assessment:
Two assignments to be conducted online (weightage of 10% each)
Mid sem exam(weightage of 30%)
Minitab exam to be conducted online (weightage of 10%)
End of sem exam(weightage of 40%)
Assessment Matrix
Course Overview: Access Course Overview