Data Analytics and Visualisation

0Running head: DATA ANALYTICS AND VISUALISATION
Summary Analytics and Visualisation
Name of the student
Name of the university
Author’s note

1DATA ANALYTICS AND VISUALISATION
Table of Contents
Introduction......................................................................................................................................3
Description.......................................................................................................................................3
Task 1 Summary Statistics...........................................................................................................4
Task 2.1 – Identification of the significant variables to be used in the Model............................4
Task 2.2 – Model Building..........................................................................................................5
2.2a - First Model........................................................................................................................5
2.2b - Second model....................................................................................................................6
Task 2.3 – Interaction Effect.......................................................................................................8
Task 3...........................................................................................................................................9
Task 3.1 – Predictive Model 1.....................................................................................................9
Task 3.2 - Probability and the log-odds.....................................................................................10
Time series for predicting turnover...........................................................................................11
Conclusion.....................................................................................................................................11
Appendix........................................................................................................................................13
Task 1.............................................................................................................................................13
Table 1: Summary Statistics for Order Quantity and Recommended...........................................13
Table 2: Correlation Coefficient for the Variables with Order Quantity.......................................14

2DATA ANALYTICS AND VISUALISATION

3DATA ANALYTICS AND VISUALISATION
Introduction
Mad Dog Craft Beer, a micro-brewery company located I Australia, has experience of
less than 15 years in brewing ale. The company produces majorly Pale Ale Beer and operates in
the Melbourne and the Victoria. The company sells its products to the buyers directly and
indirectly through the representatives of sales in pubs, bars and restaurants and bottle shops.
However, the company has grown faster in terms of production and the sales of the beers for past
two years. The rising demand for its pale ale beer has been meet by the brewing company in
2018, through increasing the capacity of brewing by 3 million litres each year.
The Mad Dog Craft Beer is expecting to shift in business environment through a
forecasting. This is because of the rising popularity due to the rise in interest in micro-brewery
culture in the operating regions. Now, it is necessary to examine the correlation between the
products and its customers in order to get a clear view of future demand for its products. So, to
fulfil the market demand a forecast is also needed which helps to get the amount of production
that is needed. The company believes that the growth of this brewing company is for the good
quality of the beer. Hence, the test for the relation between the beer produced by the company
and sells is needed. The quality of the beer is measured by 9 different parameters. The important
parameter should be identified which can describe the quality of the beer. To proceed for the
investigation of the relationship and forecasting, the data is collected through an online survey
and the data analysis works on the 200 primary observations who are the customer of the Mad
Dog Craft Beer. The variables on which the data is collected are the loyalty of the customer,
type, region, rating of the company according to the customers and the level consumption of the
products produced by the company.