Course Title: Analyse data and report results

Part B: Course Detail

Teaching Period: Term2 2017

Course Code: MATH7075C

Course Title: Analyse data and report results

School: 174T School of VE Engineering, Health & Science

Campus: City Campus

Program: C5363 - Diploma of Laboratory Technology (Biotechnology)

Course Contact: Amber Mitton

Course Contact Phone: +61 3 9925 8053

Course Contact Email:

Name and Contact Details of All Other Relevant Staff

Rauha Quazi

+61 3 9925 4277

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


MSL924001 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:

MSL925001 Analyse data and report results


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.


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.


3 Determine variation and/or uncertainty in data distributions

Performance Criteria:

3.1 Organise raw data into appropriate frequency distributions.3.2 Calculate means, medians, modes, ranges and standard deviations for ungrouped and grouped 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 Estimate the uncertainty in measurements using statistical analysis. 3.6 Determine data acceptability using statistical tests and workplace procedures.


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 as required.


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

  1. Lectures
  2. Online learning activities
  3. Computer Based tutorials

Teaching Schedule

Week No






3 July

Perform scientific calculations

Calculation of uncertainties

Significant figures

Scientific notation



10  July 

Calculating scientific quantities:  

Equations involving pH, [H+], [OH-], buffer calculations

Worksheet 1

(complete in class or at home)


17 July 

 Introduction to Statistics

Basic statistics

Descriptive Statistics

Use Minitab to compute descriptive statistics


Assignment 1 handed out


24 July 

Constructing and interpreting graphs

Correlation and regression

Use Minitab to create scatter plots and find out correlation between data sets



31 July

Control Charts

Use Minitab to plot control charts

Worksheet 2

 (complete in class)


7 August

Normal Distribution

z scores calculations

Assignment 1 due


14 August

Conducting Statistical Tests

One sample z-test and t-test

Use Minitab to conduct one sample z and t test

Worksheet 3

(complete in class)


 21 August

Mid semester exams -  no class



28 August

28 August - 1 Sept: Mid Semester Break



4 Sept

Two sample z-test and t-test

Use Minitab to conduct two sample z and t-test

Worksheet 4

(complete in class)

Assignment 2 handed out


11 Sept

Chi-square test

Use Minitab to conduct Chi-square test



18 Sept


 Use Minitab to conduct ANOVA

Worksheet 5 (5%)



25 Sept

Case studies based on all statistical tests

Assignment 2 due


2 Oct

Review of Minitab to conduct  statistical tests



9 Oct

Online Minitab exam

Online Minitab exam


16 Oct




23 Oct

 End of Semester  Exam

End of Semester Exam


Learning Resources

Prescribed Texts


Other Resources

Handouts and Online Learning materials will be provided during the course.

You need a scientific calculator to solve problems.

Overview of Assessment

online assignments/quizzes

mintab test


written tests

Assessment Tasks

Assessment task

Weighing %


Assessment 1 – Worksheets

5 Worksheets 5% each

5 x 5 = 25%

Weeks 3, 5, 7, 9, 11

Assessment 2 -  Assignments

2 Assignments 10% each

10 x 2 = 20%

Weeks 6, 12

Assessment 3 – exams

Online Minitab exam 20%

End of semester exam 35%

20 + 35 = 55%

Weeks 14, 16

Assessment Matrix

Other Information

Assessment Information

This course is graded in accordance with competency-based assessment, but which also utilise graded assessment
CHD Competent with High Distinction (80 – 100%)
CDI Competent with Distinction (70 – 79%)
CC Competent with Credit (60 – 69%)
CAG Competency Achieved – Graded (50 – 59%)
NYC Not Yet Competent
DNS Did Not Submit for assessment

  • To pass the course you need to pass, on average, each type of assessment (exams, assignments, worksheets) For example, if there are two exams you need to have an average of 50% to pass and you also need to have passed the other assessment types. You can’t make up marks from one type of assessment to another (e.g. pass the exams but fail the assignment component).
  • 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 (available online at least 24 hours before the due date. The application is lodged with the School Admin Office on Level 6, Bdg 51. Students requiring longer extensions must apply for SPECIAL CONSIDERATION.
  • For missed assessments such as exams- 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, 48 hours of the scheduled time of examination

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