Reference no: EM133665662

Quantitative Methods and Contemporary Tools

OVERVIEW
- You will be working on set of activities spanning the topics covered in the course.
- All work submitted must be original and entirely your own work, except where you use ideas, quotations, tables, diagrams, code, or any other material from writers. In such cases, you must acknowledge the source using the APA7 referencing style.
- No part of the work submitted may be used as part of any assessed work for any other academic course.

About the module activities

Introduction
Each of the four assessment activities requires you to implement and execute the components of the quantitative methods workflow. Some parts require investigations others require research which is then applied to MS Excel and the chosen data.

The various modules activities will require you to document aspects of the process you followed. Therefore, each of your module activities has one overarching requirement: Document the findings, activities and observations for each of the modules.

The key behind this type of application process is that everything you are performing within the quantitative analytics space must be repeatable so that your actions will always produce the same results.

Details

Each part of assessment work will detail necessary requirements and deliverables. All your answers, activities, and observations much be submitted via ElTonline.

- No emailed, printed, or alternative form of assessment deliverable will be accepted.
- Make sure you clearly identify each activity.
The assessment activities require familiarization with the Microsoft Excel 2016/2019 spreadsheet tool, referred to as MS Excel here on. Alternative spreadsheet tools such as LibreOffice Calc may facilitate some activities but are not supported and recommended. This is owing to the product specific requirements in the various activities such as DAX and PowerQuery.

Team/Peer Contribution
The assessment is individual work. However, discussions with your peers regarding perspectives and ideas is encouraged provided the deliverable and finding is your own work.

PART ONE - CHOOSING A PROBLEM and SOURCING DATASET/s Introduction

This assessment activity focuses on choosing a business case and sourcing of suitable data for the purpose of establishing insights and data products.

Details
Think of a suitable business scenario within which/for which you will investigate various data sources. The data could exist in various forms such as CSV to actual data from an unspecified database.
At this point, you are not expected to have a perfect set of data that offers all the insights, However, you should at a minimum be aware that the data could potentially support your business scenario.
We can assume you have the MS Excel tool configured and ready for use. During the initial examination you may have data that is not suitable for direct use in MS Excel. This would require pre-processing using a third-party tool. This is not within the scope of the assessment or course; however, you will be expected to document if the data is required to support your business case.

Requirements
- Establish a suitable business scenario that you will investigate and research. Write a clear, concise, and coherent definition of the problem.
- Evaluate the business problem and discuss why and how quantitative analysis of data can help solving this problem.
- Identify suitable data for the purposes of extracting insights and creating data products. The data sources must be publicly available. Discuss the applicability of the selected data, potential benefits, and challenges in relation to the business scenario. This entails the identification of potential insights and data products.
- Acquire the dataset/s that you have identified (the dataset/s should be submitted along with the report).

Deliverables
Prepare a preliminary report that includes the following:
• Overview (100-200 words) of the business case identifying a business reporting gap or need.
• List of data source/s and respective links/URLs - attached compressed archive/s of the respective data should not exceed 50 MB per file.
• A rationale (100-200 words) on the suitability of the above data source/s.
• A discussion (200-300 words) regarding the applicability of the data, potential insights/data products related to the business scenario.

PART TWO - DATA WRANGLING AND EXPLORATORY DATA ANALYSIS

Introduction

This assessment activity assumes that you have now acquired data that supports your business case. This module recognises the data could potentially be in a form that is not suitable for further processing and analysis. Therefore, you will apply appropriate data wrangling techniques to make your data ready for further processing and analysis. You will also use suitable graphical and non-graphical techniques to perform the exploratory data analysis.
Details
At this stage, you should have a firm grasp of the way MS Excel works. This activity will be using the MS Excel and PowerQuery features to wrangle the data into a form suitable for further processing and analysis. You will also use visualisation and analytics features in MS Excel to perform exploratory data analysis.
Requirements
In this part of the assessment, you will apply data wrangling and EDA on your data identified and acquired in the previous stage. The requirements of this part are as follows:
• Apply appropriate data wrangling techniques to ensure that your data is in suitable format and data quality issues are rectified, and production quality data is obtained. Not that the wrangling techniques that you may need to apply vary based on the initial form of the data, how tidy and clean the data is, whether any transformation or conversion required and so on. Hence, the data may require a small or significant amount of work.
• Apply EDA including graphical and non-graphical techniques to gain insights about your data, identify potential relationships and trends, outliers, important variables, etc. This step should enable you formulate valuable questions about the problem or refining existing questions. For the visual exploration of the data and drawing insights from your analysis, you can use some of the following charts (at least three types)
o Bar and pie charts
o Histograms and frequency plots
o Line graphs
o Scatterplots (bivariate data)
o Stem and leaf displays
o Box plots
o Other suitable charts
For non-graphical techniques consider using techniques such as
o Assessing central tendencies such as mean, median and mode (univariate)
o Assessing variability such as range, interquartile range (IQR), variance, standard deviation
Please note that you should discuss the interpret the results.

Prepare a report that includes the following:
• A clear, concise, and coherent description/summary of the dataset (200-300 words)
• Discussion on the data wrangling techniques you have used and rationale behind using them (200-300 words)
• A clear, concise, and coherent summary of the EDA techniques used, analysis of results, and your finding including to one or more low-level questions in 600-700 words. You may have applied various EDA techniques; however, you should mainly focus on those which have enabled you craft relevant and valuable questions about the business case.
• Attach insightful graphs, tables etc. that you have developed to support your discussion.
Expected total report word count: 1100-1300 words. PART THREE - STATISTICAL INFERENCE (PART A) Introduction
In this part of the assessment work, you will continue your analysis by focusing on the statistical inference for gaining more in-depth insights.

Details
By now you would have completed preliminary graphical and non-graphical exploratory data analysis of your data. In this activity, you will continue to work on the quantitative analysis of the data. The analysis will be progressive using a wide range of techniques from simple to more advanced, and each step should help you gain better understanding of the data and more meaningful outcomes for the next stages.

Requirements
The activity will be carried using statistical inference techniques. The following guidelines provide clues for more effective analysis.
• Review the insights and questions drawn from the exploratory data analysis. These insights will be useful for informing and setting up your inferential analysis.
• Review the original business problem or issue you were looking a solution for. From the EDA analysis, evaluate if the data (or variables) are appropriate for its intended purpose i.e., solving the business problem. At this stage, you may need to evaluate issues such as additional data that may be required/available for analysis, refining the original business problem or questions etc.
• Investigate and discuss the application of univariate and bivariate inferential analysis, for example using confidence intervals, tables, and cross-tabulation, creating categorical variables and grouping data, and or correlation analysis.
• Based on the outcome of previous stage develop and test at least one hypothesis.
• With detail and critically discuss your inferential analysis including the statistical models developed, hypothesis tests, interpretation of the test results, etc. supported by evidence (e.g., graphs).