Reference no: EM132379647

KIT714 ICT Research Principles - Semester 2, 2019

Practical: Quantitative Research Exercise

Task Length: 2,000 words max

Weighting: 20% of total assessment for this unit

Description: This practical task will engage students in a quantitative 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 quantitative data analysis and presentation of results.

In this assignment, we will be conducting:

An investigation into the current car parking situation at Chadstone Shopping Centre

Chadstone Shopping Centre installed traffic counter devices at the entrances to the 4 car parks. The devices record the time (and date) that each car enters the carpark and have been in operation for twelve months. You have been given access to aggregate data reporting the total number of cars entering each of the four carpark seach day.

Carparks

There are 4 carparks located in the Chadstone Shopping Centre Precinct.

Requirement:

Your task is to select and apply statistical analysis techniques to examine the data and derive some conclusions to the following questions:

1. Describe and illustrate the relevant data selected from the full dataset.

2. Are there differences between car park usage during school holidays and non- school holidays? School terms go from Term 1: 29/01/18 to 29/03/18, Term 2: 16/04/18 to 29/06/18, Term 3: 16/07/18 to 21/09/18, Term 4: 08/10/18 to 21/12/18.
o Select the appropriate data
o Plot data using an appropriate chart
o Perform a t-test and discuss the results
o Discuss whether a t-test is appropriate for this data

3. Are there differences in the number of cars using different terminal carparks?
o Select the appropriate data
o Plot data using an appropriate chart
o Perform an ANOVA
o Based on the ANOVA result, run t-tests to confirm differences
o Discuss whether ANOVA and t-tests are appropriate for this data

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. Thereport shouldbenomorethan 2,000 wordslength(notethatthe 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.