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1. Define and evaluate key concepts of business analytics.

ssignment Brief

Module Title

Business analytics and Intelligence

 

Assignment Number and Weighting

 

Module Code:

M121SSL

 

Assignment Title

Individual report

 

 

           

Assessment Information

This assignment is an individual work and it is designed to assess learning outcomes 1, 2, 3, 4 and 5:

Intended learning outcomes

1. Define and evaluate key concepts of business analytics.

2. Critically apply business analytics skills for decision making.

3. Critically analyse and interpret the outputs of data mining models and forecasting results for end-users.

4. Solve managerial problems and make systematic decisions by applying business data analysis techniques.

5. Have ability to apply business analytics to various international business contexts by selecting appropriate techniques.

Task One

  1. Critically analyse and explain the concept of Artificial Neural Network and Decision Tree [15 marks]

Task Two- Artificial Neural Network Analysis

You have been provided with a data file on the frequent use of social media in the UK- called ‘social_media_data_CW2.xls’

  1. Perform a descriptive analytics to illustrate the summary statistic that quantitatively describes or summarises key features of the data collected [15 marks]
  2. Perform correlation analysis for the independent and dependent variables and determine the relationship between the variables [15 marks]
  3. Predict the frequency of social media usage on society by using Artificial Neural Network technique in SPSS [NB: use ‘Impact of Social Media’ as the dependent variable] [15 marks]
  4. Interpret the data output with supporting academic literature [15 marks].

Task Three: Exponential smoothing forecasting method

Table 2 below presents the combined gross (in millions of pounds) of Porcelain Cement sales from 1999 to 2018 in the UK. Use the Exponential Smoothing forecasting method with an alpha value of 0.4 to forecast the sale of cement for 2019.

Table 2: Movie releases from 1999 to 2018

Years

Demand (actual)

 

 

 

 

1999

234

 

 

 

 

2000

243

 

 

 

 

2001

244

 

 

 

 

2002

230

 

 

 

 

2003

235

 

 

 

 

2004

225

 

 

 

 

2005

240

 

 

 

 

2006

237

 

 

 

 

2007

243

 

 

 

 

2008

226

 

 

 

 

2009

232

 

 

 

 

2010

239

 

 

 

 

2011

236

 

 

 

 

2012

232

 

 

 

 

2013

224

 

 

 

 

2014

237

 

 

 

 

2015

228

 

 

 

 

2016

234

 

 

 

 

2017

245

 

 

 

 

2018

246

 

 

 

 


a. Compute the forecasted sale of cement using an alpha value of 0.4 [5 marks]

b. Plot the data for the actual sales and the forecasted figures on the same chart. Describe the main features of the series. [10 marks]

b. Calculate the Error, Mean Absolute Deviation (MAD) error, Mean Square Error (MSE) and Mean Absolute Percentage error (MAPE). Interpret the error values. [10 marks]

Word Count

Word count= 2250 excludes the graphs and calculations

There will be a penalty of a deduction of 10% of the mark (after internal moderation) for a report exceeding 10% or more.

The word limit includes quotations, but excludes the final reference list and appendices.


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