MIS770 Foundation Skills in Data Analysis – Trimester 3, 2024 Assessment Task 2 –Individual Assignment

Category	Assignment	Subject	Management
University	Deakin University	Module Title	MIS770 Foundation Skills in Data Analysis Individual Assignment

Description

Purpose

This assignment task is aligned to the learning outcomes and skills GLO4 & ULO2, ULO3 required in applying the ideas and concepts introduced in Modules 1 and 2 to undertake Descriptive Measures, Probability Theory, and Inferences to transform raw data into information and knowledge using appropriate data analysis techniques. You will require to prepare a business report that analyses a given dataset and interprets the results to demonstrate understanding of the specific business problems posed, and that offers conclusions and recommendations that address these problems. You will use plain language to report pertinent findings in a fair, neutral and transparent manner, and present compelling evidence to support their findings. By completing this task, you will encounter with some examples of the application of data analysis within an organisation, test your understanding of the material presented in the relevant topics, and your ability to analyse data, and effectively communicate your results in a language best suited to target audience/business professionals.

Context/Scenario

InsightEdge is a larger (fictitious) company that manufactures electronic appliances. The performance of employees is an important factor in determining the success of a company. An overview of all aspects of the employees within the company is necessary in order to gain a better understanding of them. Towards the end of the year, the annual board meeting is approaching, and you have been asked to provide a summary of the results of a survey you conducted on the current employee base of your organisation. Approximately 400 randomly selected employees are included in the data set, which contains fifteen variables.

As the senior analyst, you will be responsible for analysing data and effectively communicating your findings to your target audience. 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.

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) “Income” – the amount we paid our employees last financial year in $’000.

b) “Job_Satisfaction” – how satisfied are our employees working for the organisation.

Q2. Exploring relationships between two variables

a) I would like to know if there is a link between the level of annual income (“Income”) and the number of years our employees have worked since the age of 16 (“Work_Yrs”). Historically I suspect that the more years you worked, the higher your Income becomes, but in order to assist us with future budgeting, I’d like to know if this is still 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 gender (“Gender”) and an individual’s status as a union member (“Union_membership”).

c) Further, it would be helpful if we knew if the age (“Age”) of a person any relationship to how an employee had describes their relations in the workplace with management (“Workplace_relations”).

Q3. Estimating employee measures

a) To assist the organisation with its future budgets, I would like you to estimate the number of hours our employees as a whole would work per week (“Work_Hrs”) – the days of a 40-hour week have long gone.

b) As you would realise, employee happiness with their organisation has a direct effect on a company’s culture and productivity, therefore I’m interested to know if you can estimate the proportion of all employees who are Very Proud or Somewhat Proud (“Pride”) to work for the company.

Q4. Employee claims

a) I read a report recently that indicated that the annual salary paid to staff in our industry (“Income”) was
$62,000. I’d like to think that we were paying our staff more than this figure. Is there any evidence to suggest that this is the case?

b) Another finding in that report concerned what job characteristics (“Job_preferences”) were most important to employees. It claimed that less than 40% of employees enjoyed their work. Can you also check this claim against your survey data of our employees?

Q5. Appropriate sample size

Finally, I am concerned that the sample of 400 employees is too small to provide accurate results as this seems hardly enough data. If we ever decide to survey our employees again, I would like to be able to:

a) calculate approximately the average annual income (“Income”) we are paying our staff to within $5,000, and
b) estimate the proportion of employees that are satisfied (“Job_Satisfaction”) with their job to within 3%

Specific Requirements

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 materials provided in Modules 1 and 2.
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 4 pages excluding cover sheet, and there is no need to, 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, it should be able to be read 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 Paul in the report.
Suggested Microsoft 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 Paul, 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 MIS770A2_ES_Data.xlsx.

Learning Outcomes

ULO 2 Manipulate and summarise data that accurately represents real world problems
ULO 3 Interpret and appraise statistical output to assist in real-world decision making
GLO 4: Critical thinking: evaluating information using critical and analytical thinking and judgment