Reference no: EM133672690
Descriptive Analytics and Visualisation
Learning Outcome 1: Apply quantitative reasoning skills to solve complex problems.
Learning Outcome 2: Plan, monitor, and evaluate own learning as a data analyst.
Learning Outcome 3: Deduce clear and unambiguous solutions in a form that they useful for decision-making and research purposes and for communication to the wider public.
Assessment Task - Data Analysis & Report
Tasks
Assignment one is an individual assignment with three tasks. The first task is to plan and deliver the assessment task on time. The second task is to analyse the given dataset and draw conclusions.
Finally, the third task is to convey the findings and conclusions in a written report to a person with very little or no knowledge of Business Analytics.
Specific Requirements
Case Study: Electric Vehicle (EV) Ownership
There is a lot of interest in Electric Vehicles (EVs) in Australia. Many believe EVs will be critical in achieving net zero emissions. However, vocal critics argue that there is insufficient information about who buys EVs, used for what activities, and how they are charged. Subsequently, the Sustainable Futures Research Centre secured a government grant to investigate EV Ownership in Australia.
Methodology:
A survey (n = 102) was conducted to collect data on EV owner demographics, charging behaviour and cost savings. The survey included questions on demographic information such as age, location and household type of the EV owner. It also included questions on use, distance travelled and charging frequencies. A brief description of the dataset is on page 2.
You are a Data Analyst at the Sustainable Futures Research Centre. Your team leader - Edmond Kendrick, has asked you to analyse the collected data. In particular, you are expected to perform descriptive and inferential analyses and produce a report based on your findings. Edmond's email to you is reproduced on page 3.
The dataset below contains numerous variables and details about EV owners.
Email from Edmond Kendrick
To: <<Your Name>>
From: Edmond Kendrick
Subject: Electric Vehicle (EV) Ownerships
Hi <Your Name>,
I have the following questions/issues relating to the EV Ownership dataset.
Do metro EV owners travel further than their regional counterparts?
Are fewer EV owners in metro areas using their vehicles for towing than those in regional areas?
Does the average fuel cost savings significantly differ across the household type?
Is there a difference in the proportion of EV owners who charge their vehicles at home more than five times per week based on their motivation (reason) for purchasing an EV?
Design an experiment to see the impact of locality and types of trips on the distances travelled in EVs. Please use the data in the ‘Experiment' worksheet for this experiment.
A separate study investigated the changing attitude of EV owners towards public EV charging infrastructure. An Attitude Index was used to measure the level of support for the government's approach, where higher values indicated greater support. The attitude of 12 EV owners was measured in 2022 and was again in 2023. Is there a change in the attitude? Please use the data from the ‘Attitude' worksheet for this task.
The assignment consists of three parts: Assignment Planning and Execution Tables, Analysis and Report. You must submit all three (your plan, data analysis and written report).
Guidelines for Assignment Planning and Execution Tables
This practical task aims to help you keep track of your assignment progress and submit it on time. To report how you plan your project and turn the plan into action, you must complete the tables provided in dot points as clearly as possible. Note that effective planning, execution, and completing given tasks on time are essential self-management skills.
Note: Dot point writing requires you to use 'point form', not complete sentences.
Before filling in the tables, you are strongly encouraged to watch the pre-recorded workshop 'How to plan an assignment and turn the plan into action?'
Guidelines for Data Analysis
Read the case study and questions asked by Edmond carefully. Then spend some time reviewing the data to understand the context. The analysis required for this assignment involves material covered in Module 1, with the corresponding tutorials being a helpful guide. Start the analysis by translating the worded business problems into testable propositions.
You can complete all data analysis using the Excel templates provided in the practicals. In choosing the technique to apply for a given question, keep the following in mind:
Are we dealing with a numerical variable or a categorical variable?
Are we dealing with one population, two populations or more than two populations?
Are we dealing with an independent population or a dependent population?
Each question must be answered using the most appropriate technique(s) and justify your decision where applicable.
Please formulate the hypotheses, and state them clearly in both notation and words in the Excel file.
Even though a question(s) leads you to inferential techniques, consider conducting a descriptive analysis of the data first.