Business Analytics

Running head: BUSINESS ANALYTICS 1
Business Analytics
Student’s Name:
Institutional Affiliation

BUSINESS ANALYTICS 2
Business Analytics
Q1
i The presentation of the report is good. The report explains the topic at hand using
writings supported by attractive visualizations such bar graphs and pictures. The
visualizations are of desirable quality and hence can attract readers to read to establish the
information presented in the report. The information provided is also presented in a
professional language builds the trust of the reader on the correctness of the insights.
ii The report shows that majority of retail industry players have adopted innovative
strategies. Therefore, this aids in decision making by motivating firms in the industry to
innovate to avoid losing customers.
The retailers expect a return on their investment in innovation in a short period of time
with around 80% of investors expecting returns within a period of one year. With these
retailers receiving an average return of two dollars for every dollar invested in
innovation, managers need to consider the importance of innovation in raising
productivity and competitiveness.
iii The report discusses the state of the Australian retail industry. The report highlights that
the industry is competitive and participants are keen to enhance efficiencies through the
use of innovation and technology. However, some participants tend to have been left
behind in leveraging technology. The report indicates that the industry is operating above
the country’s average in adopting technology with around 87% of retailers being either
innovative active or improvers while around 3 percent have abandoned technology
completely. The major driver of innovation in the retail sector is the improvement of
efficiency and productivity.

BUSINESS ANALYTICS 3
iv Although the report is good, the number of charts in the presentation should be reduced
without losing information. It is possible to incorporate a few visualizations that are
easily comprehensible and rich in information (Ward, Grinstein & Keim, 2015). This will
make the report shorter and information rich.
Q2
i Regression analysis can be used in cost estimation while predicting the relationship
between costs incurred and the level of business level of activity (Kaplan, 2015). For
instance, a car repair company can use regression analysis to estimate the total cost of
repairing a given number of cars. In this scenario, total variable cost is the dependent
variable while the number of cars repaired becomes the independent variable. Regression
analysis leads to development of an equation in the form of Y=a+bx such that the
dependent variable Y can be estimated given the value of the independent variable X.
ii Height and Weight Dataset
Table 1
Height (cm) Weight (Kg)
1 182 77
2 161 58
3 161 53
4 177 68
5 157 59
6 170 76
7 167 76
8 186 69