Descriptive Analytics and Visualization Assignment of AusPaper

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MIS771 Descriptive Analytics and
Visualization
Assignment 2
Future Business Decision of AusPaper
Student Name:
Student ID:
Unit Name:
Due Date:

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Table of Contents
Future Business Decision of AusPaper........................................................................1
Introduction.................................................................................................................... 3
Research Direction........................................................................................................ 4
Task 1....................................................................................................................... 4
Task 2....................................................................................................................... 5
2.1 Correlation Analysis.............................................................................................. 5
2.2 Regression Analysis.............................................................................................. 6
2.3 Logistic Regression............................................................................................... 8
Task 3....................................................................................................................... 9
3.1 Maximum Likelihood............................................................................................ 9
3.2 Predicted Probability Visualization..........................................................................10
Task 4..................................................................................................................... 12
Forecasting of Sales.................................................................................................... 12
Conclusion................................................................................................................... 13
References............................................................................................................... 14
Appendices............................................................................................................... 16

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Introduction
The Australian paper monster Auspaper has a long history of achievement underway of paper
items. The organization is a subsidiary establishment of Pinnon Paper Industries. The recorded
background of the organization is extremely promising, and they used to create relatively break
even with the measure of paper items contrasted with the aggregate items all the comparable
organizations. The significant clients had a place with two distinct market segments. The
organization used to pitch their items to the magazine and newspaper areas through direct deals
or through the merchant. The organization likewise sent out paper items to different nations of
Asia, Middle East, USA, and Europe and in various regions of India and in addition Africa.
The future issue zones were distinguished by the innovative work wing of Auspaper and a
portion of the worries annoyed the administration. The extension of online networking, alongside
expanding business sector of electronic devices was two of the essential components for likely
future decrease in the deal. The organization indented to play out a statistical surveying and they
moved toward the exploration group Chief Hugo Barra, a Ph.D. in data science and a master in
Digital Marketing at ANALYTICS7. The activity of dissecting the venture was given to the
researcher after a long discussion on the extent of the exploration.
Research Direction
The main issue was distinguished as the enlightenment of key organization together in a business
to the business condition regarding the consumer loyalty with Auspaper's working, and items
manufactured by Auspaper. The likelihood of the clients was additionally assessed with a logistic

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model for additionally understanding the pattern of the strategic alliance. Besides, a forecasting
for three quarters for the year 2017 was led for sales analysis.
Task 1
The principal assignment was to evaluate the dependent factor of the gathered information fields
of 200 clients. The descriptive estimations of the strategic alliance were found for satisfaction
level of the clients. The activity was performed utilizing Microsoft Excel Tool pack. The
satisfaction average score was found as 6.95 out of 10. Sign of very nearly 70% likely future buy
of Auspaper items was watched. The deviation of satisfaction score of 1.24 was likewise taken
note. This factor was an extremely irritating figure as 12% divergence in the negative side could
discourage the future arranging of the organization. The median was 7.05 and a Gaussian nature
of the conveyance of satisfaction score was seen with an exceptionally minor skewness of 0.09.
The mode of the information was at 5.4; this demonstrated the satisfaction level for the majority
of the clients. This pattern was not under any condition empowering for the organization. The
range of the satisfaction was noted to be 5.2 with least satisfaction level at 4.7 and most extreme
at 9.9. Investigation of 200 samples was done for this investigation and the standard error was
computed as 0.08, which gave a rough approximation to the populace Mean. The 95%
confidence interval for the satisfaction score was between the interval of 6.77 and 7.12, the less
spread confidence interval was a valuable outcome to break down the client likelihood for the
paper results of Auspaper.
The whole information set was part into two subcategories in view of the strategic alliance
preference decision of the clients. The initial segment comprised of 86 clients who liked to
proceed with future cooperation with the organization. The mean satisfaction level for those

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clients was observed to be 7.94, which was expectedly more prominent than that of the aggregate
satisfaction index. The median was at 7.9 and the mode at 7.6. Relatively ideal ordinary
dissemination for the satisfaction bend was seen with an irrelevant skewness of - 0.08. The
consistency and homogeneity for the clients were apparent from the descriptive information. The
95% confidence interval was ascertained as [7.75, 8.13]. The second sector of clients with an
inclination of ending their strategic alliance together with Auspaper was 114 in numbers. It was
seen that the majority of the clients were troubled with the administration of the Auspaper. The
mean satisfaction was 6.2 and the median was 6.3, the most critical perception was for the
median which was 5.4 for the informational data set. The distribution had a skewness of 0.26
with kurtosis of - 0.77.
Task 2
2.1 Correlation Analysis
The satisfaction of clients was the dependent variable and it was cross-checked with the
independent factors. Various correlation procedures were utilized for the reason and affiliation
levels among the elements were taken into a note.
The likely dependent variable was consumer loyalty score, which was persistent in nature. The
strategic alliance was the dependent variable which had two levels. At first correlation with these
dependent variables was taken note. With a specific end goal to limit on the exploration of
independent factors, and finish the rundown for most significant independent factors multiple

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correlation matrix was developed utilizing the exceed expectations instrument pack utilizing this
arrangement of 15 factors.
With the end goal of visual impact, at first, scatter charts were drawn. The graphs correspond to
the pattern of the dependent factor in view of the independent components. The delivery speed
was found to possess a significant and high positive (R = 0.63) correlation with consumer
loyalty; price flexibility had a low level of correlation (R = 0.03) with satisfaction. The
dependent variable had a high positive correlation (R = 0.54) with billing, image (R = 0.48),
product line (R = 0.65), complaint readdress (R = 0.59) and product quality (R = 0.51). A portion
of the factors, for example, e-commerce (R = 0.34) and technical support (R = 0.2) additionally
had a low level of positive correlation with the satisfaction of clients. The scatter charts explicitly
represented the pattern of these affiliations. Pricing was the main factor which was adversely (R
= - 0.28) corresponded with the dependent variable. The buying expectation of the clients was
hampered by the higher costs of paper results of Auspaper contrasted with other adversary
organizations. The optimistic side was the quick conveyances of the paper products, product line
variability, complaint readdress system and correct billing was the central point for client
maintenance investigation work. The business channel methods for appropriation, the diverse
locales, and the industry compose did not come into the correlation examination.
2.2 Regression Analysis
After the correlation examination, the researcher proceeded with different regression procedure
utilizing MS Excel tool pack. The principal model comprised of fourteen factors including the
strategic alliance together of the clients with the organization. It was watched that advertising
was not a noteworthy factor for the regression demonstrate with p-value of 0.98 and coefficient

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of - 0.001. The model was rebuilt by expelling advertisement factor and warranty on products
was observed to be irrelevant with a p-value of 0.85 and likelihood coefficient of - 0.015. The
model was recreated again without the factor, warranty, and step by step, delivery speed of the
organization (p-value of 0.66), billing transparency (p-value of 0.58), new product launching in
advertise (p-value of 0.21), technical support for customers (p-value of 0.22), pricing of paper
products (p-value of 0.09), and complaint readdress system (p-value of 0.06) were additionally
disposed of from the model because of level of inconsequentiality levels. The last model
comprised of six elements, which were product quality, e-commerce, and product line variability,
the image of the company, price flexibility, and type of future strategic alliance probability with
the clients. The numerous direct regression displays was concluded as underneath (DeHoratius &
Raman, 2008).
Y =0 . 34 X1−0 . 33 X2+0 . 4 X3+ 0. 57 X 4+0 . 25 X5+ 0. 59 X6−1 .2
Y = satisfaction level of the customers
X1 = Product quality
X2 = E-commerce
X3 = Product line
X4 = Image
X5 = Price flexibility
X6 = Strategic alliance level

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The model depicted the way that for one unit level of increment in product quality (without
changing other factors) will expand the satisfaction level of the clients by 34%. The comparable
choice was feasible for other five components (Gelman, 2014).
2.3 Outside ANZ Regression (Interaction) Model
Outside ANZ region, a multiple regression model was used to measure level of interaction
between previously identified variables. Among all independent factors, five factors were
significantly correlated to customer satisfaction. Product quality, complaints readdress system,
image of the company, pricing of paper products, and strategic alliance type were the significant
variables. These variables were taken into consideration to contruct the new regression model.
The final model was as below,
Y =0 . 32 X1+0 . 0 .39 X2 +0 .28 X3−0. 14 X4+ 0 .89 X5 +1. 55
Y = Customer satisfaction
X1 = Product quality
X2 = Complaint readdress system
X3 = Image
X4 = Price of products
X5 = Strategic alliance level