2,000 words or approximate equivalent. Note: Part of your submission involves visualisations (in Excel) which ultimately account for a proportion of this word count. Accordingly, your report (Word document) should be approximately 3 pages in length.
Two files (Excel, Word) electronically via CloudDeakin.
MIS770 Foundation Skills in Data Analysis DEPARTMENT OF INFORMATION SYSTEMS AND BUSINESS ANALYTICS DEAKIN BUSINESS SCHOOL FACULTY OF BUSINESS AND LAW, DEAKIN UNIVERSITY Assignment Two Analysis of Electric Vehicle Data 1.0 Particulars • Due: Week 9, Thursday 19th January 2023, 8:00 pm (AEST). • Marks: 30%. • Words: 2,000 words or approximate equivalent. Note: Part of your submission involves visualisations (in Excel) which ultimately account for a proportion of this word count. Accordingly, your report (Word document) should be approximately 3 pages in length. • Submission: Two files (Excel, Word) electronically via CloudDeakin. Email submissions will not be accepted. Note: Do not convert your Word document to pdf format. • Notes: This assignment is to be completed individually. Please ensure you are familiar with the Extension Request and the Late Penalties rules governing assignments in the Faculty of Business and Law (see details below). 1.1 Assurance of Learning This assignment assesses the following Graduate Learning Outcomes and related Unit Learning Outcomes: Graduate Learning Outcome (GLO) Unit Learning Outcome (ULO) GLO4: Critical thinking: evaluating information using critical and analytical thinking and judgment ULO2: Manipulate and summarise data that accurately represents real world problems ULO3: Interpret and appraise statistical output to assist in real-world decision making 2.0 Overview The purpose of this assignment is to investigate a dataset that has been produced based on available information on a sample of electric vehicles (EVs). You now need to interrogate this dataset in order to answer questions posed by the Australian Electric Vehicle Council. Ultimately, you will need to analyse the data, interpret the results, and then draw appropriate conclusions. The aims of the assignment are to: • provide you with some examples of the application of data analysis • test your understanding of the material presented in the relevant topics • test your ability to analyse data and effectively communicate your results in a language best suited to target audience Before attempting the assignment, make sure you have prepared yourself well. At a minimum, please read the relevant sections of the prescribed textbook and review the learning materials provided in modules 1 and 2 (i.e., Topics 1 to 7). _________________________________________________________________________________________________________________________ MIS770 Foundation Skills in Data Analysis Assignment Two (T3, 2022) Page 1 _________________________________________________________________________________________________________________________ MIS770 Foundation Skills in Data Analysis Assignment Two (T3, 2022) Page 2 2.1 Scenario The Australian Electric Vehicle Council wants you to process and analyse the data set and then answer several questions. The questions you need to answer are contained in the following memorandum. Assume that your readers do not have an analytics background, so it’s important that you utilise “plain, easy to understand language” in your answers. If you believe you need to include any technical terms, then you must explain these in a clear and succinct manner using layman’s terms. 2.2 Memorandum Date: To: From: Subject: 20 December, 2022 You, Data Analyst Jane Smith, CEO Analysis of Electric Vehicle Data Dear YourName, Can you please carry out an analysis of the Electric Vehicle data (contained in the file EVData.xlsx) and prepare a report containing answers to the following questions. Q1. Summaries of key variables of interest Can you please provide me with separate summaries of the following variables, just by themselves? In other words, please investigate each variable individually without reference to any other variable in the dataset. (a) “Efficiency_WhKm” – average consumption of the battery in watt hours for each kilometer traveled. (b) “BodyStyle” – style/size of the car. Q2. Exploring relationships between two variables (a) I would like to know if there is a link between the top speed of EVs (“TopSpeed_KmH”) and their price (“Price”). I suspect that the higher the top speed, the higher the price will be, but I’d like to know if this is actually the case. Therefore, I’d like you to establish from your sample data if there is any relationship between these two variables. (b) I’m also interested to establish if there is a relationship between the drive type (“PowerTrain”) and the style (“BodyStyle”). (c) Further, it would be helpful if we knew if the drive type (“PowerTrain”) has any relationship with how efficient an EV runs (“Efficiency_WhKm”). Q3. Estimating EV measures (a) I would like you to estimate how far EVs overall can drive on a single charge (“Range_Km”). (b) I’m also interested to know if you can estimate the proportion of all EVs which are perceived as larger cars (i.e., SUVs or Pickups) (“BodyStyle”). Q4. Claims about EVs (a) I read somewhere that acceleration (i.e., 0 to 100 km/h) for EVs (“AccelSec”) was 7 seconds. I think that acceleration is lower than this figure for EVs (they can go from 0 to 100 km/h in less than 7 seconds). Is there any evidence to suggest that this is the case? _________________________________________________________________________________________________________________________ MIS770 Foundation Skills in Data Analysis Assignment Two (T3, 2022) Page 3 (b) Another claim concerned market segments (“Segment”). The claim was that less than 20% of EVs belonged to Segment D. Can you also check this claim against your survey data? Q5. Appropriate sample size Finally, I am concerned that the sample of 92 EVs is too small to provide accurate results as this seems hardly enough data. If we ever decide to repeat the analysis, I would like to be able to: calculate approximately the average range (“Range_Km”) to within 15 kilometers. Therefore, how many EVs would we need to include in the next analysis to satisfy this requirement? Regards, Jane 3.0 Report Requirements • Your report must have a cover sheet containing your personal particulars and the Unit details, an executive summary, introduction and conclusion. • Your report should be no longer than 3 pages excluding cover sheet, and there is no need to include any visualisations (i.e., Charts and Tables) or Appendices in the Report. • The Charts/Graphics and Tables you create are only to be placed in the Data Analysis file (i.e. the Excel spreadsheet) and not reproduced in the report. • Your report is meant to be a stand-alone document. That is, readers should be able to read it without looking at the data analysis. To this end, do not refer to the visualisations as “as you can see from Figure 1 etc”. You need to interpret your data analysis visualisations for Jane in the report. • Suggested Word formatting for the report: Single‐line spacing; no smaller that 10‐ point font; page margins approx. 25mm, and good use of white space. • Set out the report in the same order as in the originating Memorandum from Jane, with each section (question) clearly marked. • Use plain language and keep your explanations succinct. Avoid the use of technical or statistical jargon. As a guide to the meaning of “Plain Language”, imagine you are explaining your findings to a person without any statistical training (e.g., someone who has not studied this unit). What type of language would you use in that case? • Marks will be lost if you use unexplained technical terms, irrelevant material, or have poor presentation/ organisation. • All Microsoft Excel output associated with each question in the Memorandum is to be placed in the corresponding tab in the file EVData.xlsx 3.1 Data Analysis Instructions/Guidelines In order to prepare a reply to Jane’s memorandum, you will need to examine and analyse the dataset EVData.xlsx thoroughly. Jane has asked a number of questions and your data analysis output (i.e., your charts/tables/graphs) should be structured such that you answer each question on the separate tab/worksheet provided in your Excel document. There are also five extra tabs in EVData.xlsx and you should use the various templates contained in these tabs in your “Confidence Interval”, “Hypothesis” and “Sample Size” answers. In order to effectively answer the questions, your data analysis output needs to be appropriate. Accordingly, you’ll need to establish which of the following techniques are applicable for any given question: • Summary Measures (e.g., descriptive statistics, Inc. outlier detection, percentiles). • Comparative Summary Measures (i.e., descriptive statistics, outlier detection and percentiles for multiple values of a variable). • Suitable tables (such as a frequency distribution) and charts or graphics (such as histograms, box plots, pie charts, bar/column charts, polygons) that will illustrate more clearly, other important features of a variable. • Scatter Diagrams (used to visually establish if there is a relationship between two numeric variables). • Cross Tabulations (sometimes called contingency tables), used to establish the relationships (dependencies) between two variables (see Additional Materials under Topic 2 – Creating Cross Tabulations in Excel using Pivot Tables). • Confidence Intervals. You can assume that a 95% confidence level is appropriate. We use confidence intervals when we have no idea about the population parameter we are investigating. Additionally, we would use confidence intervals if we were asked for an estimate. You should use the relevant Excel templates provided in the dataset and copy them to the applicable question tab. • Hypothesis Tests. You can assume that a 5% level of significance is appropriate. We use hypothesis tests when we are testing a claim, a theory or a standard. You should use the relevant Excel templates provided in the dataset and copy them to the applicable question tab. • Sample size calculation: You can assume that a 95% confidence level is appropriate. You should include comparisons for 90% and 99% and a recommendation for the appropriate sample size. • To answer some questions, you may need to make certain assumptions about the data set we are using. Mention these in your data analysis, where relevant. There is no need to mention this in the report. Note: There is an appendix at the end of each chapter of the prescribed textbook which describes the basic Excel steps associated with that topic. Chapters 1 to 9 are applicable for this assessment. 3.2 Submission Your completed assignment should be submitted in two separate files: • Report (Part A): A word document of no more than 3 pages (excluding title/cover page) that must not contain any charts/tables/graphs. (Note: Do not submit a pdf document in lieu.). Please name your word document Assignment2_yourstudentid.docx • Data Analysis (Part B): An Excel document containing separate tabs/worksheets with charts/tables/graphs for each question. Please note that all interpretations should be presented in your “Report” and the Excel document should only contain your intermediate analysis and final output. Please (re-)name your Excel document Assignment2_yourstudentid.xlsx The assignment is to be submitted to the MIS770 assignment box in CloudDeakin before 8 pm, Thursday 19th January 2023. Please ensure you include your name and student details in your Word document as well following the above file naming convention. Failure to follow this convention may lead to a delay in receiving feedback and marks. 4.1 Faculty of Business and Law Assignment Extension Procedures Information for students seeking an extension BEFORE the due date If you wish to seek an extension for this assignment prior to the due date, you need to apply via the online Assignment Extension Tool in MIS770 unit site. You must provide a reason for the extension as well as your supporting documentation (e.g., medical certificate) and a draft of your assignment. Not providing both items would result in rejection of your request. This needs to occur as soon as you become aware that you will have difficulty in meeting the due date. To support you in using the tool, the Learning Innovation team has prepared the following short video: https://video.deakin.edu.au/media/t/1_g9rtrqow Students who request an extension due to Covid are required to provide evidence of a positive PCR test or a reply notification that they have registered a positive RAT test where possible (i.e. for students located in Australia) or other evidence (for students located offshore). This process needs to occur as soon as you become aware that you will have difficulty in meeting the due date. _________________________________________________________________________________________________________________________ MIS770 Foundation Skills in Data Analysis Assignment Two (T3, 2022) Page 4 https://d2l.deakin.edu.au/d2l/lp/navbars/1192499/customlinks/external/11392 https://d2l.deakin.edu.au/d2l/lp/navbars/1192499/customlinks/external/11392 https://d2l.deakin.edu.au/d2l/home/1192499 https://video.deakin.edu.au/media/t/1_g9rtrqow Please note: Conditions under which an extension will normally be considered include: • Medical – to cover medical conditions of a serious nature, e.g., hospitalisation, serious injury or chronic illness. Note: temporary minor ailments such as headaches, colds and minor gastric upsets are generally regarded as not serious medical conditions. • Compassionate – e.g., death of a close family member, significant family and relationship problems. • Hardship/Trauma – e.g., sudden loss or gain of employment, severe disruption to domestic arrangements, victim of crime. Note: misreading the due date, assignment anxiety or travel will not be accepted as grounds for consideration. Information for students seeking an extension AFTER the due date If the due date has passed; you require more than two weeks extension, or