# Course Title: Apply workplace statistics to the food industry

## Part B: Course Detail

Teaching Period: Term1 2011

Course Code: MATH5247

Course Title: Apply workplace statistics to the food industry

School: 155T Vocational Health and Sciences

Campus: City Campus

Program: C5184 - Diploma of Food Science & Technology

Course Contact: Bruce Henry

Course Contact Phone: +61 3 9925 4545

Course Contact Email: bruce.henry@rmit.edu.au

Name and Contact Details of All Other Relevant Staff

Nominal Hours: 40

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

VBP034 - Process and interpret physical data pertaining to the food industry

Course Description

This unit covers the skills and knowledge required to effectively use statistics in the work place.

National Codes, Titles, Elements and Performance Criteria

 National Element Code & Title: VBP070 Apply workplace statistics to the food industry Element: Analyse processes using statistical Performance Criteria: 2.1 Using workplace data, indices of significance and variance are calculated and interpreted 2.2 Using workplace data, indices of probability are calculated and interpreted 2.3 Correlation and regression analysis techniques are applied to workplace data Element: Calculate and report statistical data. Performance Criteria: 1.1 Data collected is represented in graphs, tables, averages and percentages as required. 1.2 Using workplace data, indices of variability are calculated and interpreted.

Learning Outcomes

Analyse processes using statistical
Calculate and report statistical data.

Details of Learning Activities

• Class discussions
• Note taking
• Data collection
• Graphing activities
• Problem solving
• Practical experiments
• Use of calculator
• Use of computer, eg Excel

Teaching Schedule

Week Learning Objectives
Week 1 INTRODUCTION TO STATISTICS
1.1 The Population and the Sample
1.2 Descriptive Statistics
1.3 Statistical Inference
1.4 Qualitative Data
1.4.1 Frequency Distribution
1.4.2 Relative Frequency Distribution
1.4.3 Bar Graphs and Pie Charts

Class Activity
Week 2
QUANTITATIVE DATA: TABULAR & GRAPHICAL
1.1 Frequency Distribution
1.2 Relative Frequency Distribution
1.3 Cumulative Frequency & Cumulative Relative Frequency Distribution
1.4 Histogram
1.5 Frequency Polygon

Class Activity
Week 3 MEAURERS OF LOCATION AND DISPERSION
1.1 Mean
1.2 Median
1.3 Mode
1.4 Percentiles

Class Activity
Week 4 MEASUERS OF DISPERSION
1.1 Range
1.2 Variance
1.3 Standard Deviation
1.4 Coefficient of Variation

Class Activity
Week 5 INTRODUCTION TO PROBABILITY
1.1 Experiments and Sample Space
1.2 Assigning Probabilities to Experimental Outcomes
1.3 Events and their Probabilities
1.4 Some Basic Relationship of Probability

Class Activity
Week 6 DISCRETE PROBABILITY
1.1 Random Variables
1.2 Expected Value
1.3 Variance
1.4 Expected Value of the Sum of Random Variables

Class Activity
Week 7 Revision of all work covered in the Semester
Week 8 Written Test
Week 9 CONTINUOUS PROBABILITY DISTRIBUTIONS
1.1 Normal Distribution
1.2 Standard Normal Probability Distribution
1.3 Computing Probabilities for Any Normal Distribution

Class Activity
Week 10 SAMPLING
1.1 Simple Random Sampling
1.2 Sampling from Finite and Infinite Populations
1.3 Point Estimation

Class Activity
Week 11 SAMPLING DISTRIBUTION
1.1 Sample Mean, SD and Proportion
1.2 Standard Error

Class Activity
Week 12 SAMPLING DISTRIBUTION
1.1 Central Limit Theorem

Class Activity
Week 13
INTRODUCTION TO EXCEL AND SPSS
1.1 Inferential Statistics

Class Activity
Week 14 1.2 Parametric and Non parametric Statistics
1.3 Hypothesis testing
Class Activity
Week 15 Revision of all work covered in the Semester
Week 16 Final Exam

Learning Resources

Prescribed Texts

References

 Statistical Quality Control for the Food Industry. Hubbard,M. (1990) Chapman and Hall Australian Food Statistics 2003, Dept of Agriculture, Fisheries and Forestry, Australia www.abs.gov.au Australian Bureau of Statistics

Other Resources

Overview of Assessment

Assessments for this course consist of:
• Class activities
• Assignments
• Exam

The following assessment methods will be used:

• Assignment sworth 50%. Projects involve the student collecting, analysing and interpreting data relevant to the food industry.

• Test worth 25%. Question and answer test with some theory questions involving interpretative answers.

• Final exam worth 25%. Short question and answer test with some theory questions involving interpretative answers.

Student must pass each Assessment task to demonstrate Competence. Students may demonstrate excellence in all tasks to receive a Credit or higher Grade.
Students will receive written feedback on all assignments within 2 weeks of due date.

Assessment Matrix

 Task Element 1.1 Element 1.2 Element 2.1 Element 2.2 Element 2.3 Assignment 1 √ √ Assignment 2 √ √ √ Test √ √ Exam √ √ √ √ √

Other Information

This course has 40 nominal hours. This will comprise approximately 30 hours of classroom teaching, 2 hours of Individual and group assessment sessions
and 8 hours of structured individual and group study and research

Course Overview: Access Course Overview