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BUS708 Statistics and Data Analysis

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BUS708 Statistics and Data Analysis

 BUS708 Statistics and Data Analysis

Statistical Modelling Assignment 

 1 OVERVIEW OF THE ASSIGNMENT

This assignment will test your skills of collecting and analysing data to answer a specific business problem. It also gives you the opportunity to apply the theories you have learned in this course such as finding numerical summaries, displaying with appropriate graphs and using statistical inferences to solve business problems, including constructing hypotheses, test them and interpret the findings. You may have to use two Data sets.

One Data set will be sent to you via KOI student email individually and you need to find or collect another dataset. Suppose you are working for an agency who analyse NSW transport system data to make a recommendation to improve public transport system. You will be given series of research questions. Use your knowledge that you gain from this course to answer these questions by displaying appropriate outputs of Excel, StatKey or Wolfram alpha. Use these answers to write an executive summary which might be a valuable recommendation to Transport NSW.   

2 TASK DESCRIPTION: WRITTEN REPORT

There are two datasets involved in this assignment: Dataset 1 and Dataset 2, detailed below. Dataset 1: You will receive an email that contains a dataset that is specifically allocated to you. This dataset is a subset of a data Opal Tap on and Tap Off Location - 8th to 14th August 2016 individual sample file, provided by the Transport for NSW Open Data  and has been edited to only include a subset of the cases and variables. The original dataset can be obtained from https://opendata.transport.nsw.gov.au/dataset/opal-tap-on-and-tap-off and it is under the license of Creative Commons Attribution 3.0 Australia. Data dictionary of the edited dataset is given in the

following table. 

                  

Dataset 2: Collect data (e.g. via a survey) that will answer research question given in section 3. There is no requirement about the number of variables, sampling methods and sample size, but you need to justify your approaches in Section 1 (see below).  

 

 



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