Part B: Course Detail

Teaching Period: Term1 2025

Course Code: MATH7095C

Course Title: Analyse data and report results

School: 535T Social Care and Health

Campus: City Campus

Program: C5434 - Diploma of Laboratory Technology

Course Contact: Rauha Quazi

Course Contact Phone: +61 3 9925 4277

Course Contact Email: rauha.quazi@rmit.edu.au

Name and Contact Details of All Other Relevant Staff

Namrita Kadalbajoo

namrita.kadalbajoo@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

MSL924005 Process and interpret data

Course Description

This unit of competency describes the skills and knowledge to perform scientific calculations, analyse trends and uncertainty in data and report results within the required timeframe.

This unit of competency applies to technical officers and laboratory technicians working in all industry sectors.

National Codes, Titles, Elements and Performance Criteria

National Element Code & Title:	MSL925006 Analyse data and report results
Element:	1. Perform scientific calculations
Performance Criteria:	1.1 Ensure raw data are consistent with expectations and reasonable ranges 1.2 Calculate scientific quantities involving algebraic, power, exponential and/or logarithmic functions 1.3 Ensure calculated quantities are consistent with estimations 1.4 Present results using the appropriate units, uncertainties and number of significant figures
Element:	2. Analyse trends and relationships in data
Performance Criteria:	2.1 Determine linear and non-linear relationships between sets of data 2.2 Prepare and analyse control charts to determine if a process is in control 2.3 Identify possible causes for out-of-control condition 2.4 Follow workplace procedures to return process to in-control operation
Element:	3. Determine variation and/or uncertainty in data distributions
Performance Criteria:	3.1 Organise raw data into appropriate frequency distributions 3.2 Calculate statistical parameters of grouped and/or ungrouped data 3.3 Interpret frequency distributions to determine the characteristics of the sample or population 3.4 Calculate standard deviations and confidence limits for means and replicates 3.5 Determine data acceptability using statistical tests and workplace procedures
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 4.2 Determine appropriate actions in consultation with supervisor
Element:	5. Report results
Performance Criteria:	5.1 Use charts, tables and graphs to present results in the required format 5.2 Verify that entry of data and results are correct 5.3 Prepare reports and records in a format and style consistent with their intended use and workplace guidelines 5.4 Communicate results within the specified time and in accordance with workplace confidentiality and security guidelines

Learning Outcomes

Details of Learning Activities

The course will be delivered using:

1. Theory face to face classes
2. Face to face learning activities using Canvas
3. Computer Based tutorials using Minitab Software

Teaching Schedule

Teaching Schedule, MATH7095, Analyse Data & Report Results

The classes for this course run 3 hours a week 

2025 Teaching and Assessment schedule 

  

WK No	Week starting	Topic	Comments
1	10 Feb	Perform scientific calculations, Calculation of uncertainties, Calculating scientific quantities, Significant figures, Scientific notation and Basic Statistics
2	17 Feb	Equations involving pH, [H+], [OH-], Ka, pKa, Kb, pKb, Kw, Ks and pKs buffer calculations Determine linear, logarithmic, exponential, and power relationships Radioactivity (half-life, dose, activity, and exposure)
3	24 Feb	Introduction to Statistics Basic statistics Descriptive Statistics Using Minitab to compute descriptive statistics
4	3 Mar	Attempt AT1 in class
5	10 Mar	Continue with Statistics and Minitab and errors/uncertainty
6	17 Mar	Construction of frequency distribution tables Construction of Histograms, frequency plots, stem and leaf plots, boxplots, and scatter plots Constructing and interpreting graphs  2nd attempt for AT1	Release AT2
7	24 Mar	Continue with previous week
8	31 Mar	Mid Sem break
9	7 Apr	Correlation and regression Use Minitab to create scatter plots and find out correlation between data sets Regression lines and interpretation of correlation coefficients
10	14 Apr (Good Friday week)	Probability and Normal probability plots Normal Distribution 3.      z scores calculations	Upload AT2 on Canvas
10		Mid sem Break: 18 – 25 April
11	28 Apr	Pareto diagrams, Shewhart control chart CuSum/complex Control charts
12	5 May	Continue with previous week and 2nd Attempt for AT2
13	12 May	Continue with Control Charts
14	19 May	Revision
15	26 May	AT3, End of semester assessment, in the class
16	2 Jun	Resubmissions
17

Learning Resources

Prescribed Texts

Course Notes/Handouts will be provided during the semester and will be available on Canvas

References

In addition to the course notes, links to resources will be provided in the Canvas

Other Resources

Overview of Assessment

Assessment may include:

• knowledge tests
• practical skills test
• practical logbooks
• presentations
• group work
• research
• lab reports
• assignments

 

Assessment Tasks

The assessments will be conducted as follows:

1.To be assessed as Competent in this course, you will need to complete each assessment task to a satisfactory standard. You will receive feedback from the teacher within given time-frame (usually within two weeks of assessment submission) of each assessment task. You should refer to the assessment brief which is available through Canvas for full assessment criteria and due dates.
To successfully complete the course, you need to achieve a satisfactory result for every assessment.
AT1
AT2
AT3

For each assessment you will be given up to two (2) attempts, however, to be granted the second attempt at any assessment, your first attempt must be an appropriate attempt to try and gain a satisfactory outcome. For example, you must appropriately attempt each question or aspect of the assessment task. 

If your first attempt fails to meet the above standard, you may not be eligible for a second attempt at that task.
A third (3rd) attempt can only be offered after discussions between teacher and the Program Coordinator and is not automatic

 

Assessment Matrix

Other Information

This course is graded in accordance with competency-based assessment

CA:   Competency Achieved 
NYC: Not Yet Competent
DNS: Did not Submit for Assessment
SEC: Student Engagement Ceased

To pass the course you need achieve a satisfactory result for all assessments. Students may be given additional opportunities to demonstrate competence. 

Late work that is submitted without an application for an extension (see below) will not be corrected.

APPLICATION FOR EXTENSION OF TIME FOR SUBMISSION OF ASSESSABLE WORK - A student may apply for an extension of up to 7 days from the original due date. They must lodge the application form  Assessment extension (Links to an external site.)  at least 24 hours before the due date. The application should be emailed to the program Coordinator (rauha.quazi@rmit.edu.au). Students requiring longer extensions must apply for SPECIAL CONSIDERATION.

• For missed assessments such as tests- you (& your doctor if you are sick) must fill out a special consideration form. This form must be lodged online with supporting evidence prior to, or within, 5 days of the scheduled time of the assessment https://www.rmit.edu.au/students/student-essentials/assessment-and-results/special-consideration

• Plagiarism is the presentation of the work, idea or creation of another person as though it is your own. It is a form of cheating and is a very serious academic offence that may lead to expulsion from the University. Plagiarised material can be drawn from, and presented in, written, graphic and visual form, including electronic data and oral presentation. Plagiarism occurs when the origin of the material used is not appropriately cited. It also occurs through enabling plagiarism, which is the act of assisting or allowing another person to plagiarise or to copy your own work. Please make sure you consider this carefully in completing all your work and assessments in this course and if you are unsure about whether you might have plagiarised, seek help from your teacher.

Course Overview: Access Course Overview