CMP7205 Applied Statistics—PG CWK Assignment Brief 2024-25 | BCU

CMP7205 Assessment Information:

Learning outcomes of CMP7205: 

Completion of this assessment will address the following learning outcomes:

1. Analyse and examine a variety of statistical techniques that can be applied to the extraction of information from data sets.
2. Plan, select and employ a variety of statistical techniques and where appropriate, use a data analytics or statistical software tool.
3. Evaluate the results of statistical techniques and a statistics or data analytics tool to a given scenario.
4. Communicate effectively in a professionally prepared report which meets the needs of an organisation.

CMP7205 Task:

Report your statistical analysis on a reasonably complex dataset(s) in a professional manner, using appropriate probabilistic and/or statistical techniques implemented with modern statistical software.

Style: Report

Rationale:

The rationale of this assessment is to analyse statistical information using modern methods and tools, and report statistical findings in a professional manner. Essentially the report will challenge the students to:

• identify a set of questions that can be answered via applied statistics;
• examine and justify a number of statistical techniques that can be used to extract information from datasets;
• read the information about the datasets to determine how to use them;
• utilise statistical software to use statistical methods and produce results in a suitable form;
• evaluate and discuss the statistical trends or hypotheses;
• and report the overall argument using excellent standards of writing that are highly demanded in a work environment.

Description:

This assignment reflects a typical data analysis task in any type of organisation. Professional data problems often involve examining given data or even looking for appropriate datasets online, identifying what kind of questions can be asked of that data and then answering those questions to drive business value. It is common for managers to not know exactly what information can be extracted from any number of given datasets. Managers in a professional organisation can expect Masters graduates in Big Data Analytics to use their initiative to apply appropriate statistical tools and techniques to datasets. For this assignment you will be taught R but you can use other tools as well.

This assessment requires the students to explore related data sources that open up significant statistical questions to apply a breadth of applied statistical methods. The report must identify suitable statistical questions, justify a list of statistical methods, apply these methods to produce aptly presented results, round it off with a critical appraisal of how well the statistical questions have been answered and report it all in an excellent standard of writing. Additional information further below gives more details on how to organise the report.

Datasets:

Multiple recommended data sources have been provided on this module’s Moodle page; however, the students can ask permission for using data of their individual interest with the module coordinator prior to submission. It is strongly recommended that the students do this by the end of Week 6.

Note that a data source may contain multiple datasets and the students can use as many datasets as they see fit; however, they must properly cite and describe the datasets in their report.

Also note that datasets can be presented in various formats and some have missing data. To understand the datasets and crucial information concerning the data such as missing values and data types, do not forget to read any accompanying notes which might be available with the datasets. Discuss missing data in your report and how you handle such data instances.

Look up software methods to upload data from specific data files and detect missing data from within.

CMP7205 Additional information:

The report must follow the structure below:

• Title of report;
  
  
• Name, Student ID, and program of study of the student;
  
  
• Table of contents;
  
  
• Executive Summary: briefly introduce the problem, major questions and interesting findings of your report. Although present at the start of the report, this must be written after the rest of the report is complete and must be no longer than half a page;
  
  
• Section 1 (Introduction): describe the purpose of the report - introduce the problem domain with suitable citations and list a set of related statistical questions;
  
  
• Section 2 (Methodology): list and justify the number of statistical techniques selected (such as those taught) to answer the previously outlined questions (or intermediate questions within) by showing how they are apt and what information can be extracted from them. This concerns marking criterion 2 listed later.
  
  
• Section 3 (Datasets): describe and justify the datasets used to show what information is contained in the datasets and how it aids to answer the relevant questions. If the description is very long, then summarise the key information and detail the columns in the datasets in appropriate appendices. Also, properly cite the dataset in the References section and include their exact hyperlinks;

• • Section 3.1 (Data Pre-processing): discuss any data pre-processing that is required to prepare the data for subsequent analysis.

• Section 4 (Results and Discussion): conduct the statistical analysis and report the results. Show how the statistical assumptions required for applying a statistical test are fulfilled. Discuss and evaluate the results to effectively answer the questions outlined earlier;

• • Detail the results in tables and figures as appropriate. Each table and figure must be numbered, and must have appropriate legends (if required) and captions. The captions must be a set of grammatically complete sentences (up to 3 lines long) that concisely describe the information in the tables and the figures. No such table and figure should be included that is not discussed in the text. The numerical comparisons should be supported by appropriate tests of statistical significance.

• Section 5 (Conclusions): summarise the key findings of your report so that if someone does not have the time to go through the whole report, he/she can still understand the important results.
  References must be written out as per Harvard Referencing Style.