| Category | Assignment | Subject | Business |
|---|---|---|---|
| University | Deakin University | Module Title | MIS171 Business Analytics |
| DUE DATE: | Monday, 26 May 2025, by 8:00 pm (Melbourne time) |
| Assessment: | Assessment Task 3 - Data analysis with written report - Individual |
The assignment requires that you analyse a data set, interpret, and draw conclusions from your analysis, and then convey your conclusions in a written report. The assignment must be completed individually and must be submitted electronically in CloudDeakin by the due date. When submitting electronically, you must checkthat you have submitted the work correctly by following the instructions provided in CloudDeakin.
Hard copies or assignments submitted via email will NOT be accepted. The assignment uses a data set which can be downloaded from Cloud Deakin. The assignment focuses on materials presented up to and including Week 11. Following is an introduction to this scenario and detailed guidelines.
In an interconnected world, data analytics has emerged as a powerful means of pinpointing deficiencies, monitoring advancements, and guiding strategies to tackle global concerns. Foremost among these concerns are the Sustainable Development Goals (SDGs)—particularly SDG 4 (Quality Education)and SDG 5 (Gender Equality)—which strive to guarantee inclusive, equitable education and lifelong learning for all, while simultaneously advancing gender equality and empowerment for everyone.
Originally adopted in 2015, the SDGs constitute a universal appeal from every United Nations Member State to eradicate poverty and inequality, safeguard the planet, and ensure that all individuals can thrive in terms of health, justice, and prosperity by 2030—without leaving anyone behind (WHO1). Within this framework, SDG 4 and SDG 5are particularly notable for their mission to reshape the landscape of quality education and gender equality on a global scale. SDG 4 targets "inclusive and equitable quality education and the promotion of lifelong learning opportunities for all" (UN2), emphasizing improvements in literacy, expanded educational access, and continuous learning. SDG 5 focuses on "achieving gender equality and empowering all women and girls" (UN3), seeking to eliminate discrimination, violence, and other harmful practices in all aspects of life. These goals underscore the crucial interplay between education and gender equality in driving overall economic growth, social inclusion, and environmental stability. To learn more about these goals, their targets, and ongoing progress, visit the United Nations' official SDG website, which offers extensive resources and updates. Engaging with these materials will enrich your understanding of the worldwide efforts to create a more just and equitable future (Sustainable development goals: https://sdgs.un.org/goals).
This assignment is designed to engage your critical thinking, problem-solving, and analytical skills through the use of descriptive analytics on the given dataset. You are tasked with conducting univariate and bivariate analyses, calculating some probabilities, performing hypothesis testing, and building confidence intervals to analyse and comprehend the status of quality education and gender equality across various countries and regions. Building upon Assignment 1's interactive dashboard/data visualization, your challenge is to dig deeper into the dataset to extract meaningful insights and patterns that illustrate the advancements and obstacles in meeting these global objectives.
A question, accompanied by guidelines highlighted in blue, are presented below. You are required to submit your Excel file containing your data analysis, along with a report that explains the outcomes of your analysis and two recommendations. Given that your audience may not have training in business analytics, your report must present the results in plain, straightforward language. A template has been provided for your use.
Do You Need Assignment of MIS171 Assessment 3 Question
Order Non Plagiarized AssignmentMultiple Linear Regression Modelling (consider α = 2%) As Human Development Index (HDI) is crucial for evaluating the effectiveness of national development strategies, build a multiple regression model to predict HDI. Your model should provide
v.Complete the Multi-Collinearity summary table which is in the Conclusion section of the Correlation worksheet. This table summarises which Independent Variables are to be eliminated from the regression model due to multi-collinearity.
vi.Scatter diagrams- in the section marked "Scatter Diagrams" (below the Correlation Table section on the "Correlation" worksheet) generate two scatter diagrams, for:
(c)Using the SDG dataset as your reference complete the following steps, on the "Regression Model"spreadsheet in the Excel file that has been provided (the data set includes the dummy variables you have created and excludes the Independent Variables which have been eliminated due to multi-collinearity or being uncorrelated with the Dependent Variable):
i. Using the "Regression" option in Excel's Data Analysis ToolPak build a multiple regression model.
ii. If your first iteration of the overall model is found to be significant, in a stepwise fashion, sequentially (one at a time) remove the Independent Variables that are least likely to be contributing to any significant change in the Dependent Variable.
(d) Once you have created a regression model where all the remaining Independent Variables are contributing significantly to a change in HDI, copy the Summary Output of your final multiple regression model and paste it into the Output section of the "Regression Model" spreadsheet in the Excel file that has been provided,
i.In the Conclusion section of the "Model" spreadsheet,
(e)Using the final multiple regression equation (from step (d)
(i)), i.In the Predictionssection of the "Regression Model" spreadsheet in the Excel file that has been provided, for the scenario outlined below:
The provided Excel file includes multiple sheets, labelled "Data Description", "Data" and a worksheet for each question. The "Data Description" sheet describes all the variables used in the "Data" and is copied below for your convenience.
The analysis section you submit should be limited to the Correlation and Regression Model worksheets of the Excel file. These are the only worksheets which will be marked. Your analysis should be clearly labelled and grouped around each question. Poorly presented, unorganised analysis or excessive output will be penalised.
In the Conclusionsection of each worksheet there is space allocated for you to write a succinct response to the questions. When drafting your Conclusion, make sure that you directly answer the questions asked. State the important features of the analysis in your Output section. Responses in the Conclusion section will be marked.
Use the Outputsection for your analysis to complete the analysis as directed and supports your response to the questions (which you will write in the Conclusion section). Analysis in the Output section will be marked, please make sure your analysis is complete, clear, and easy to follow. You may need to add rows or columns to present your analysis clearly and completely.
It is useful to produce both numerical and graphical analysis. Sometimes something is revealed in one that is not obvious in the other.
Use the Workings section for calculations and workings that support your analysis. The Workings section will not be marked.
Having analysed the data, including answers (in technical terms) to the Data Analysis questions from Part 1 you are required to provide a formal report. Given that your audience may not have training in business analytics, your report must present the results in plain, straightforward language. The audience will only be familiar with broad generally understood terms (e.g., average, correlation, proportion, and probability). They will need you to explain more technical terms, such as quartile, mode, standard deviation, coefficient of variation, correlation coefficient, and confidence interval, etc.
In section 1 of the report, provide a brief interpretation of your findings of the Correlation and Regression analyses. In section 2 of the report, provide TWO (2) recommendations that could help countries improve their Human Development Index (HDI) scores. Your recommendations should be based on the analysis conducted in this assignment, insights from previous assignments, and any additional relevant analysis that enhances the impact of your recommendations.
Consider the following in framing your recommendations:
Ensure that all your recommendations are directly informed by your data analysis. Avoid including any commentary not supported by your data analysis.
Highest marks will be awarded to students who draft distinct (i.e., different) recommendations, and whose recommendations take into account a broad range of (data-supported) considerations. When exploring data, we often produce more results than we eventually use in the final report, but by investigating the data from different angles, we can develop a much deeper understanding of the data.
This will be valuable when drafting your written report. It is useful to produce both numerical and graphical statistical summaries. Sometimes something is revealed in one that is not obvious in the other. You are allowed approximately 1,000 words (950 to 1,050 words) for your report. Remember you should use font size 11 and leave margins of 2.54 cm. A templateis provided for your convenience. Carefully consider the following points:
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