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KIT714 ICT Research Principles – Semester 2, 2020
Practical Quantitative Research Exercise
Type: In-Semester (Individual Assignment)
Task Length: 2,000 words
Weighting: 20% of total assessment for this unit
Due Date: 11:55pm, 5 October 2020
Submission:
date. Completed Assignments need to be uploaded to MyLO by the due
Description: This practical exercise will engage students in a qualitative research
exercise that will enable them to directly deploy skills, tools and techniques covered in the unit. Each student will be required to complete the exercise and prepare a written report that displays their level of research understanding and competence in qualitative data analysis and interpretation.
In this assignment, we will be conducting:
An investigation of the impact of technology on the processing capacity of letters, small and large parcels in Australia Post facilities.
You have been presented with data across three Australia Post facilities (Tullamarine, Mascot and Brisbane) from January 2018 to December 2019. To cope with increasing demand, Australia Post has installed an automated sorting station for parcels in Tullamarine and an artificial intelligence-based prioritization system for all items in Mascot. Brisbane has not had any new technology implemented over the same time period.
CSV
Type heading Description
Date date A date between 01/01/2018 to 31/12/2019
Year integer Year between 2018 to 2019
Facility string Australia Post processing area
Letters integer Can include greeting cards, bills, A4 documents, personal letters
Small Parcels integer Parcels weighing less than 5kg
Large Parcels integer Parcels weighing 5kg or more
Requirements:
Your task is to select and apply statistical analysis techniques to examine the data and derive some conclusions to the following questions:
1. Formulate a research question for this study.
2. Select the appropriate data to conduct a statistical test to determine if there is a significant difference between 2 independent groups.
• Describe and plot relevant data selected from the full dataset using an appropriate chart.
• Formulate the appropriate hypotheses.
• Discuss and justify whether parametric or non-parametric test would be suitable for this data.
• Run the appropriate statistical test and discuss the results.
3. Select the appropriate data to conduct a statistical test to determine if there is a
significant difference between 2 dependent groups.
• Describe and plot relevant data selected from the full dataset using an appropriate chart.
• Formulate the appropriate hypotheses.
• Discuss and justify whether parametric or non-parametric test would be suitable for this data.
• Run the appropriate statistical test and discuss the results
4. Select the appropriate data to conduct a statistical test to determine if there are significant differences between more than 2 independent groups.
• Describe and plot relevant data selected from the full dataset using an appropriate chart.
• Formulate the appropriate hypotheses.
• Discuss and justify whether parametric or non-parametric test would be suitable for this data.
• Run the appropriate statistical test and discuss the results.
The output of your analysis will be a brief report (including title, abstract, brief introduction, results and discussion) in Springer’s Lecture Notes in Computer Science (LNCS) format. The report should be no more than 2,000 words length (note that the LNCS format has very wide margins) and should be submitted in PDF.
Analysis Tool Advice:
You may use any suitable tools for analysing the data. For instance, descriptive statistics can be produced by Excel, Python, R, and many other packages equally well, whereas Python and R support many non-parametric tests that Excel does not. You may need to do some data preparation in Excel in order to organize the data appropriately for the comparisons you wish to perform in another tool.
Submission:
Submit your completed report in PDF to [Assignments] on the unit’s MyLO site by 11:55pm, Monday 5 October 2020. The report must comply with the LNCS format for conference papers.
Lecture Notes in Computer Science is a long-running series of edited books, predominantly containing conference proceedings. There are templates available for both LaTeX and MS Word. On that page look at the sections titled Templates, sample files and useful links – LaTeX2e Proceedings Templates or Microsoft Word Proceedings Templates, which contain zip files of the relevant templates.
Ask questions:
Questions about approaches you are considering using or how to use the LaTeX template can be directed to Mihai.Neagoe@utas.edu.au.
Criteria
Outstanding (HD) Very Good (DN) Good
(CR) Adequate
(PP) Poor
(NN)
Description of dataset (10%) Provided a complete and comprehensive description of the relevant data selected form the dataset with appropriate charts
Provided a mostly complete description of the relevant data selected from the dataset with
appropriate charts Provided a good description of the relevant data selected from the dataset with appropriate charts Provided a basic description of the dataset without
appropriate charts Provided no description of the dataset
Hypotheses and
Statistical tests (50%) Hypotheses are all clearly stated and are aligned with the statistical tests being performed.
Correct use of statistical tests in relation to the stated hypotheses with follow-up tests where appropriate incorporating description and discussion of significance.
Excellent discussion provided as to the appropriateness of the tests for the dataset and suggestions of alternatives available.
Hypotheses are mostly clearly stated and are aligned with the statistical tests being performed.
Mostly correct use of statistical tests in relation to the stated hypotheses with follow-up tests where appropriate incorporating description and discussion of significance.
Very good discussion provided as to the appropriateness of the tests for the dataset and suggestions of alternatives available. Hypotheses contain minor errors but are aligned with the statistical tests being performed.
Mostly correct use of statistical tests in relation to the stated hypotheses.
Good discussion provided as to the appropriateness of the tests for the dataset and suggestions of alternatives available. Hypotheses contain major errors but are somewhat aligned with the statistical tests being performed.
Mostly correct use of statistical tests.
Adequate discussion provided as to the appropriateness of the tests for the dataset. No hypotheses stated. Mostly correct use of statistical tests but no discussion provided.
Presentation of results (25%) Presentation is clear with appropriate choice of chart type incorporating error bars showing variance where appropriate.
Axes are clearly labelled and appropriate for making clear comparisons.
Captions fully describe figures.
Presentation is clear with appropriate choice of chart type incorporating error bars showing variance where appropriate.
Axes are clearly labelled and appropriate for making clear comparisons.
Captions mostly describe figures. Presentation is clear with appropriate choice of chart type. Axes are clearly labelled and appropriate for making comparisons.
Captions fully describe figures. Presentation is clear with appropriate choice of chart type.
Axes are clearly labelled and appropriate for making comparisons.
Captions adequately describe figures. Presentation is unclear with inappropriate choice of chart type. Captions do not describe figures.
Overall presentation (15%) Findings answer the research question and demonstrate insight and incorporate information not found within the given data.
Report is clear, well-structured and contains sufficient detail following the LNCS format.
Report is mostly free of grammar and spelling errors. Findings answer the research question and demonstrate some insight.
Report is clear, well-structured and contains sufficient detail following the LNCS format.
Minor spelling and grammatical errors. Findings mostly answer the research question and demonstrate limited insight. Report is mostly clear and wellstructured following the LNCS format.
Some spelling and grammatical errors. Findings somewhat answer the research question and demonstrated little insight.
Organization of the report could be improved but is generally comprehensible. Report does not follow the LNCS format.
Several grammatical or spelling mistakes. Findings do not answer the research question.
Report is poorly organized and difficult to follow, or contain many grammatical or spelling errors.
Report does not follow the LNCS format.