# Course Title: Analyse data and report results

## Part B: Course Detail

Teaching Period: Term2 2016

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 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 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

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 as required

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

1. Lectures

2. Online learning activities

3. Computer Based tutorials

Teaching Schedule

Teaching Schedule(Based on Week starting)
 4th July • Introduction to Statistics • Basic Statistics • Descriptive Statistics 11th July • Continue with previous week • Equations involving pH, [H], [OH], buffer calculations, Ka, pKa, Kb, pKb, Kw • Henderson – Hasselbach equation 18th July • Correlation • Linear and Non-Linear relationship between data 25th July • Normal Distribution • Control Charts 1st  August • Continue with Control Charts • Types of Control charts 8th August 1. Normal Distribution 2. z scores calculations 15th  August • Calculating confidence limits for the means • More on Normal Distribution • Revision for mid sem 22nd August Mid semester exams 29th August Student Vacation 5th Sept Conducting statistical tests z-test 12th Sept •t-test and using Minitab 19th Sept • Conducting Chi-square and using Minitab 26th Sept • Conducting ANOVA  using Minitab 3rd Oct • Case studies based on all statistical tests • Valid measurement and data acceptability tests 10th Oct • Continue with previous week. 17th Oct Revision/ Catch up 24th 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

To demonstrate competency in this course you need to successfully complete each one of the following pieces of Assessment:

1. Four online assignments/quizzes to be conducted online (10% each)
2. Minitab exam- using and interpreting statistical analysis(20%)
3. In Class Presentation - Data Collection and Analysis(10%)
4. End of semester exam (30%)

(All assessment tasks/online and presentation will be conducted during class time in the class room)

Assessment Matrix

Other 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 and assignments etc.) 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 prac 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 http://www1.rmit.edu.au/students/assessment/extension) 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 http://www1.rmit.edu.au/students/specialconsideration

Course Overview: Access Course Overview