# Course Title: Process and interpret data

## Part B: Course Detail

Teaching Period: Term1 2019

Course Code: MATH7074C

Course Title: Process and interpret data

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: amber.mitton@rmit.edu.au

Name and Contact Details of All Other Relevant Staff

Nominal Hours: 70

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

None

Course Description

This unit of competency covers the ability to retrieve data, evaluate formulae and perform scientific calculations, present and interpret information in tables and graphs and keep accurate records. The unit requires personnel to solve problems of limited complexity where the information may be less obvious, but not contradictory, and can be determined by direct reasoning.

National Codes, Titles, Elements and Performance Criteria

 National Element Code & Title: MSL924001 Process and interpret data Element: 1 Retrieve and check data Performance Criteria: 1.1 Store and retrieve data using appropriate files and/or application software 1.2 Verify the quality of data using workplace procedures 1.3 Rectify errors in data using workplace procedures Element: 2 Calculate scientific quantities Performance Criteria: 2.1 Calculate statistical values for given data 2.2 Calculate scientific quantities using given formulae and data and estimate uncertainties 2.3 Ensure calculated quantities are consistent with estimations and expectations 2.4 Report all calculated quantities using the appropriate units and correct number of significant figures Element: 3 Present data Performance Criteria: 3.1 Present data in clearly labelled tables, charts and graphs 3.2 Graph data using appropriate scales to span the range of data or display trends 3.3 Report all data using the appropriate units and number of significant figures Element: 4 Interpret data Performance Criteria: 4.1 Interpret significant features of tables, charts and graphs, including gradients, intercepts, maximum and minimum values, and limit lines 4.2 Recognise and report trends in data Element: 5 Keep accurate records and maintain confidentiality Performance Criteria: 5.1 Transcribe information accurately 5.2 Verify the accuracy of records following workplace procedures 5.3 File and store workplace records in accordance with workplace procedures 5.4 File all reference documents logically and keep them up-to-date and secured 5.5 Observe workplace confidentiality standards

Learning Outcomes

Details of Learning Activities

• Lectures
• Worksheets
• Online learning activities

Teaching Schedule

2019 teaching schedule for Process & Interpret Data

 Week Week starting Topic 1 11th Feb SI units Scientific Notations Significant figures 2 18th Feb Calculating basic statistics for given data 3 25th Feb Levey Jennings chart Measurement conversions and micro-measurements 4 4th March Continue with previous week 5 11th Mar Indices, Index lawsPerform calculations using indices 6 18th Mar Ratio & Proportion Direct & Joint Variation Percentages and calculations with percentages 7 25th Mar Continue with previous week and Revision 8 1st April Mid Sem Assessment Week 9 8th April Concentrations & Dilutions 10 15th April Graphs Represent and interpret data in graphical form 22nd April Easter break 11 29th Apr Linear Equations Formulas and Substitution 12 6th May Continue with previous week 13 13th May Logarithms 14 20th May Areas and Volumes 15 27th May Continue with previous week 16 3rd June Assessment week

Learning Resources

Prescribed Texts

References

Other Resources

Overview of Assessment

online quizzes

simulated data activities

written tests

Assessment:

To receive a competent result, the student needs to be assessed as satisfactory in each of the three tasks.

Set of 2 online quizzes

Ongoing completion of following three activities (25th March to 20th May)
a. Maintain Simulated Data Entry Object
b. Perform calculations within the simulated laboratory
c. Report, check and maintain records

Mid semester and End semester tests

 Assessment Week starting Online Quiz 1 25th Feb Online during class time in the class room Online Quiz 2 18th Mar Online during class time in the class room Maintain Online Database 20th May Ongoing activity from 20th March to 21st May(To be completed using a simulated database) Mid sem Assessment 1st April Details TBA End sem Assessment 3rd  June Details TBA

Assessment Matrix

Other Information

Assessment information

This course is graded in accordance with competency-based assessment

CA Competency Achieved
NYC Not Yet Competent
DNS Did Not Submit for assessment

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 (http://www1.rmit.edu.au/students/assessment/extension) at least 24 hours before the due date. The application should be emailed to the program Coordinator (amber.mitton @rmit.edu.au). Students requiring longer extensions must apply for SPECIAL CONSIDERATION.

• For missed assessments 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 http://www1.rmit.edu.au/students/specialconsideration

• 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.

NOTE: This course is equivalent to MATH7088C (MSL924003 Process & interpret data)

Course Overview: Access Course Overview