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Business Analytics: Concepts, Regression Analysis, and Forecasting

Task One-Business Analytics Concepts

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.

This is an individual Assignment.


Task One-Business analytics concepts

a.Describe what you have learned about the data mining including its relevant steps. Give proper example for each
b.Critically discuss and analyse five published papers which have used Data Mining techniques with proper explanation. The technique, its application and the results need to be interpreted properly

Task Two- Regression Analysis

An analysis is done about 20 selected hotels considering some characteristics. Customer satisfaction in overall as well as each characteristic has been gathered and reported in Table 1.
Table 1- Customer satisfaction rate of twenty hotels

Hotel    Overall    Comfort    Amenities    In-House Dining
H1    92.68    91.50    87.80    95.70
H2    94.73    92.60    85.10    98.60
H3    92.93    97.90    97.00    90.40
H4    93.05    90.50    93.70    94.00
H5    90.00    92.00    83.80    92.10
H6    90.20    90.40    83.00    95.70
H7    89.73    95.90    87.20    87.90
H8    91.90    91.50    94.50    88.80
H9    86.70    93.60    81.80    87.70
H10    89.63    92.50    85.20    88.40
H11    86.18    87.80    81.90    85.50
H12    90.55    92.00    95.00    87.60
H13    84.28    88.50    74.20    89.20
H14    81.90    91.00    89.60    71.50
H15    85.50    91.90    72.90    90.60
H16    86.33    95.30    77.00    88.50
H17    88.08    91.40    79.30    90.80
H18    88.25    95.80    76.40    88.40
H19    84.15    94.00    68.20    89.20
H20    86.08    94.40    76.30    88.80

a.Determine and interpret that which variable is more correlated to the overall satisfaction. Is it highly or lowly correlated? What do you conclude?
b.Plot the data and find the multiple regression model for Overall and Comfort. Interpret it clearly
c.Identify the slope, the intercept in (b), then interpret the values
d.How much is the R-square value? Properly interpret its value.
e.What will be happened if we only consider one independent variable in the regression analysis. Discuss on the results comparing with the result of multiple regression.

Task Two- Regression Analysis

Task Three- Forecasting

Suppose that you have gathered sales data of company XYZ from 2014-2020 in different quarters. You are going to consider the company sales value and to forecast the company amount of sales in 2021 in different quarters. Look at the gathered data of previous years related to the amount of sales in each quarter which have been reported in Table 2.
2014    1    370.0                                        
2014    2    585.0                                        
2014    3    930.0                                        
2014    4    493.7                                        
2015    1    433.3                                        
2015    2    624.3                                        
2015    3    1010.8                                        
2015    4    510.2                                        
2016    1    449.6                                        
2016    2    648.3                                        
2016    3    1045.0                                        
2016    4    528.9                                        
2017    1    472.0                                        
2017    2    685.8                                        
2017    3    1120.8                                        
2017    4    576.8                                        
2018    1    517.0                                        
2018    2    758.6                                        
2018    3    1244.4                                        
2018    4    629.9                                        
2019    1    558.9                                        
2019    2    810.1                                        
2019    3    1311.0                                        
2019    4    663.5                                        
2020    1    588.0                                        
2020    2    851.5                                        
2020    3    1376.0                                        
2020    4    688.0                                        

a.Use the data of mentioned table to compute the four-period moving average and enter your values in the appropriate columns. [5 marks]

b.Plot the data and describe the main features of the series.

c.Calculate the Centered Moving Average (CMA)/Baseline. Interpret it.

d.Calculate the Trend and interpret the trend.

e.Determine the Seasonality (St) and interpret it properly

f.Forecast the revenue for 8th year

g.Calculate the Error, mean absolute percentage error (MAPE), Mean Square Error (MSE) and Mean Absolute Deviation (MAD).

h.Write a brief report to explain and evaluate and make comments on the error variables, the forecasted and actual revenues.

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