Describe descriptive, predictive and prescriptive analytics

Describe descriptive, predictive and prescriptive analytics with addressing all techniques which you have learned during the lectures. Give proper example for each [8 marks]

Describe descriptive, predictive and prescriptive analytics
Task One-Business analytics concepts [25 marks]

Firstly, describe descriptive, predictive and prescriptive analytics with addressing all techniques which you have learned during the lectures. Give proper example for each [8 marks]

Secondly, critically discuss and analyse five published papers which have used mentioned techniques in the Task one (a) with proper explanation. Further, the technique, its application and the results need to be interpreted properly [17 marks]

Task Two- Regression Analysis [25 marks]
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.

Firstly, determine and interpret that which variable is more correlated to the overall satisfaction. Is it highly or lowly correlated? What do you conclude? [5 marks].

Secondly, plot the data and find the simple regression model for Overall and Comfort. Interpret it clearly [5 marks].

Thirdly, identify the slope, the intercept in (b), then interpret the values [5 marks].

Additionally, how much is the R-square value? Properly interpret its value. [5 marks].

Finally, what will be happened if we only consider one independent variable in the regression analysis. Discuss on the results of simple regression comparing with the result of multiple regression. [5 marks].

Task Three- Forecasting [50 marks]
Suppose that you have gathered sales data of a company from 2013-2019 in different quarters. You are going to to consider the company sales value and to forecast the company amount of sales in 2020 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.

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