Reference no: EM133130117

7BSP1361 Data Analytics - University of Hertfordshire

Individual Presentation

Learning Outcome 1: Recommend which visualisation and summary techniques to apply to data in a business context.

Learning Outcome 2: Determine, critically evaluate and advise on which aspects of statistical methodology apply to problems occurring in a business context.

Learning Outcome 3: Design methods to collect/gather data in a way that is suitable for the associated business problems to be analysed.

Learning Outcome 4: Create summaries of data appropriate to the business problem that exists.

Learning Outcome 5: Communicate the nuances and ambiguities of statistical analyses they [the students] have undertaken and conclusions drawn from these.

Learning Outcome 6: Evaluate output produced by software packages used to implement statistical techniques.

Assignment - Individual Presentation on Supervised Learning

Description of the assignment:

Each student will be provided with a unique dataset, and should carry out statistical analysis using R. The analysis must be carried out using the four supervised learning methods covered in the class. These four methods are decision trees, logistic regression, discriminant analysis and k-nearest neighbours.

You are required to produce presentation slides (up to 20 pages, no note is allowed) describing your analysis and outlining your results. The presentation should be aimed at a lay person with some very basic statistical knowledge. You are also required to submit the R code for the analysis you have conducted. You are only required to submit the presentation slides (PowerPoint) and the accompanying R code (all code in a single *.R file, no other format will be accepted).You are NOT allowed to submit extra note(s). All the relevant information must be contained in the slides. No actual presentation is to take place.

Attachment:- Data_Analytics.rar

Attachment:- Supervised Learning.rar