Data Analysis Name of University: Course ID: 3 Data Analysis

Running head: DATA ANALYSIS
Data Analysis
Name of Student:
Name of University:
Course ID:

DATA ANALYSIS1
Table of Contents
Introduction:...............................................................................................................................3
Data collection process:.............................................................................................................3
Data Description:.......................................................................................................................3
Findings of data analysis:...........................................................................................................4
Task 1.....................................................................................................................................4
Task 2.....................................................................................................................................4
Task 2.1..............................................................................................................................4
Task 2.2..............................................................................................................................5
Task 2.3..............................................................................................................................5
Task 3.....................................................................................................................................6
Task 3.1..............................................................................................................................6
Task 3.1.a...........................................................................................................................6
Task 3.1.b...........................................................................................................................6
Task 4.........................................................................................................................................7
Task 5.........................................................................................................................................7
Appendix:...................................................................................................................................8
Task 1:....................................................................................................................................8
Task 2...................................................................................................................................11
Task 2.1............................................................................................................................11
Task 2.2............................................................................................................................13

DATA ANALYSIS2
Task 2.3....................................................................................................................................15
Task 3...................................................................................................................................19
Task 3.1.a.........................................................................................................................20
Task 3.1.b.........................................................................................................................22
Task 4...................................................................................................................................26

DATA ANALYSIS3
Introduction:
“Pinnon Paper Industries” has a subsidiary named “AusPaper”. The Australian
company, “Pinnon Paper Industries” is has an extended history in local production of
products of paper. “AusPaper” trades products of papers to the two market segments like “the
newspaper industry” and “magazine industry”. The newspaper industries that receive paper
products are Herald Sun and Australian Financial Review. The magazine industries that
obtain paper products are Homes & Gardens and Men’s Style magazine. The products are
indirectly retailed to the customer and through a broker also.
The “AusPaper” company exports the paper-products to more than 75 countries of
Indian subcontinent, Europe, Asia, Middle East, Latin America, and Africa. In last few years,
“AusPaper” purchased more than 690000 tonnes of products as well as produced 619000
tonnes of paper products to the markets locally and overseas.
It causes a change in choices of end-consumers alike the preferences of online
magazines, preferences of readers across newspapers and preference of social media. More of
it, the consumers are developing to undertake a tactical move to have a strong strategic
partnership with their customers. These days, “AusPaper” management textures the
requirement for ensuring a stable customer base and supremely a solid strategic alliance with
their consumers of magazine and newspaper industry. Not only is that “AusPaper” setting up
to insert a formal process to be capable of prospecting future financial turnovers with the
support of historical data, but also develop their business with proper process. In spite of
successful operations and firm financial turn-overs over the last two decades, “AusPaper”
company is forecasting a vivid shift within the forthcoming seven years in the business
environment.
Data collection process:
The concerns of “AusPaper” highlights the contracted managers of firms purchasing
from “AusPaper”. It invigorated them to contribute in an online survey. The gathered data is
accompanied by other assembled information. It tabulated the data regarding sales of
“AusPaper” warehouse, its sale and manageable through the decision support system.
Data Description:
For the analysis in MS Excel, the researcher used the add-ins “RealStats”. The
logistics regression and stepwise multiple regression are executed with the help of this add-
ins. The researcher clarified his objectives from the analysis to summarise the major research
questions. The analysis with the assistance of considered factors clarify consumer loyalty
with operations of a firm. The information intends to discover crucial factors that estimate
satisfaction of consumers perceived from previous purchases from “AusPaper”. The analysis
aims to increase minute insights into variables that estimate the "likelihood of “AusPaper”
customers building strategic alliance" with the firm. The report analytically focuses to
develop a predictive model to anticipate the turnover of AusPaper in the 2nd, 3rd and 4th
quarters of 2017. For the forthcoming financial year 2017, the analysis would demonstrate
whether “AusPaper” would be in a decent position or not.

DATA ANALYSIS4
200 perceptions along wide 18 factors are included in the data file. Mostly two kinds
of data are resent in this database. First one is the perception of performance of “AusPaper”
on 13 characteristics that are measured utilizing 0-10 scale where “0” denotes “Poor” and
“10” is “Excellent”. The other information links to include outcomes and business
connections, for example, amount of consumers and length of purchase association and in
addition quarterly turnover operations of "AusPaper".
Findings of data analysis:
Task 1.
Summary of frequencies of Strategic alliance:
 The frequency distribution and frequency table of the variable “Extent to which the
customer/respondent perceives his or her firm would engage in strategic
alliance/partnership with “AusPaper”” determines that out of 200 samples, 114
samples incurred the strategic alliance or strategic partnership.
 On the other hand, 86 people conveyed that they are engaged in strategic alliance or
relationship. The percentage share of these two cases are 57% and 43% respectively.
Summary of Customer satisfaction:
 The average customer satisfaction with past purchases from “AusPaper “is found to
be 6.95.
 The standard deviation indicates the spread of the distribution of customer satisfaction
with purchases from “AusPaper” that provides the value 1.24.
 The middle most value in terms of median of the satisfaction data set is 7.05.
 The location measures refer that 25% of the bottom values are less than 6 and 25% of
the top values are more than 7.9.
 The mode is 5.4 that indicates that the frequency is found highest when customer
satisfaction rate 5.4.
 The minimum customer satisfaction of previous purchases from “AusPaper” is 4.7
and maximum customer satisfaction of previous purchases from “AusPaper” is 9.9.
 Hence, the customer satisfaction with previous purchases from “AusPaper” ranges
between 5.2.
 The customer satisfaction level of slightly rightly and positively skewed. The
graphical visualization indicates that its left tail is longer than its right tail.
Task 2.
Task 2.1.
The 15 samples are detected for analysis and tabulated samples are attached in the
appendix section of the assessment file. These chosen variables are – Cstmr_Type,
Indst_Type_Dummy, Size_Dummy, Region_Dummy, Distn_Sys_Dummy, Prdct_Qual,
E_Comm, Cmplnt_Supp, Advert, Prdct_Line, Image, Pricing, Warranty, New_Prdct, Billing.

DATA ANALYSIS5
“Sats” is assumed to be a dependent variable. All the variables except “Sats” are assumed to
be independent variables. The analyst is interested to build a predictive model with the single
dependent and multiple (fourteen) independent variables.
Task 2.2.
The value of R2 is not authenticate in this analysis as it might contain multi-
collinearity. Therefore, adjusted R2 is the suitable measure of finding association among
variables and goodness of fit. The predictive multiple regression model refers that altogether
the 14 predictors explain 83.3% variability of the response variable. Stepwise regression
ultimately selects 8 significant factors that are customer type, dummy of size, dummy of
distribution system, product quality, complaint residuals, product line, image and new
product.
From ANOVA table of the multiple regression model, the analyst observes the p-
value of the whole model (0.0). Hence, the model is fitted well and the predictors all together
predict the model well with 95% probability. The significant p-values of the independent
factors refer that four factors have p-values less than 0.05. These variables are- Cstmr_Type
(p-value = 0.0000), Size_Dummy (p-value = 0.0000), Distn_Sys_Dummy (p-value = 0.0000),
Prdct_Qual (p-value = 0.0000), Cmplnt_Res (p-value = 0.0000), Prdct_Line (p-value =
0.009), Image (p-value = 0.0000) and New_Prdct (p-value = 0.016). Hence, these four
variables have linear and statistical significant association with dependent variable “Sats” at
5% level of significance. Rest of all the variables have insignificant effect on the response
variable as the calculated p-values for those variables are less than 5%. The negative and
positive slopes or beta values refers the negative or positive association between that the
variables. All the factors have positive association with dependent variable.
Task 2.3.
The analyst in the next part of the analysis caused that the depth and breadth of
“Product line” of “AusPaper” is a significant estimator of the variable “Customer
Satisfaction”. The previous analysis referred that the strength of this association may vary
according to the location of customers.
Among 200 consumers, 81 customers are from in Australia and New Zealand. 119
consumers are from outside Australia and New Zealand. Three multiple regression models
are executed with the help of four variables that are product line, region, customer
satisfaction and interaction effect of region and product line.
Here, 0 = Outside ANZ and 1 = ANZ region. The multiple regression model has
considered the interaction variable of “Region” and “Product line” as predictor variables. The
interaction variable is calculated multiplying two predictor variables. Hence, the predictor
variables are “Region”, “Product line” and “Interaction effect”. The response variable is as
usual as “Customer satisfaction”.
In the multiple regression model, all the three variables Product line, Region and
Interaction are linearly, positively and significantly associated with “Customer satisfaction”
where product line has co-efficient is 0.865218 and p-value is 0.0. Here, “Region” has co-
efficient 2.927282 and significant p-value is 0.0003 and “Interaction” has co-efficient has (-
0.55504) and significant p-value is 0.0. Therefore, among the three variables “Product line”,
“Region” and the “Interaction effect”, “Product line” and “Region” have linear significant

DATA ANALYSIS6
influence on the dependent variable “Customer satisfaction”. The regression model has p-
value less than 0.05. Hence, according to the most suitable predictive model, all the three
predictors most suitably predicts the dependent variable – Customer satisfaction.
Task 3.
Task 3.1.
The main target of the data analysis is to finalise an advanced predictive model
utilising key variables that impact the “likelihood of building a strategic alliance of
partnership” with “AusPaper”. The advanced model building analysis takes into account five
factors that are “Product Quality”, “Product Line”, “Personnel Image”, “Flexibility” and
“Competitive Pricing”.
The response of logistic regression model is the dichotomous binary variable used as
“Strategic Alliance”. In the first model, the predictor variables are “Personnel Image” and
“Product Line”. In the second model, the predictor variables are “Product Quality” and “Price
Flexibility”. The probabilities of strategic alliance are found with the two logistic models.
Task 3.1.a.
“Personnel Image” and “Product Line” are the predictor variable and “Strategic
Alliance” is dependent variable in the predicted logistic regression model. The predictive
regression model could be stated as-
............... (1)
The p-values of two predictor variables, “Product Line” and “Personnel Image” in this
logistic regression model are both 0.0. As, p-value is less than level of significance, both the
dependent variables, “Personnel Image” and “Product Line” are significant explanatory
variables at 5% level of significance.
Task 3.1.b.
“Product Quality” and “Price Flexibility” are predictor variables and “Strategic
Alliance” is dependent variable in the predictive regression model. It is given as-
............. (2)
The calculated p-values of two predictor variables “Product Quality” and “Price
Flexibility” in the logistic regression model are 0.0 in both cases. As, calculated p-values are
less than level of significance, both the explanatory variables are significant at 5% level of
significance.

DATA ANALYSIS7
Task 4.
The futures prediction of “AusPaper” is necessary for the growth of business and
sales. To predict the future turnover amount, the analyst considered “Time” as explanatory
variable and “Turnover ($’000)” as response variable. The variable “Turnover ($’000)”
indicates for total turnover amount within the time span. The variable “Time” is actually the
chronological frequency of quarters starting from 1st quarter of 2008 to 1st quarter of 2017.
The estimated turnover amounts of the 2nd, 3rd and 4th quarters of 2017 are found to be
$4531.955, $4991.969 and $5043.73 respectively.
Task 5.
As an outcome, the quarterly turnover amount of “AusPaper” also has enlarged
significantly. The quarterly turnover amounts of 2nd, 3rd and 4th quarter are more in 2017 than
any other quartiles of previous year. Same as first quarter, the turnover amounts of other
quarters also have grown effectively in 2017. The future of “AusPaper” seems to be
promising. The research analysis concludes that the consumers of “AusPaper” has a high
satisfaction level. Most of the consumers are allied in strategically. Strategic alliance, product
quality, E-communication and Image has significant influence on the Customer satisfaction.
Not only that, “Product line”, “Region” and their “Interaction” effect has significant
relevance to the satisfaction of customers. “Image” and “Product line” significantly predicts
the types of Strategic alliance of “AusPaper”. “Product quality” and “Price flexibility” of
“AusPaper” also significantly influence the dependent variable “Strategic alliance”.
As per discussion, the analysis determines the predicted possibility of building
strategic alliance with varying levels of “Product Quality” and “Product Flexibility” in
several perceptions. Conversely, the constant proportion to the “Product Line” and
“Personnel Image” for effecting “Customer Satisfaction” is also asserted. The superior values
of independent variables are growing “Customer Satisfaction” and types of “Strategic
alliance” with “AusPaper”. The organization should focus on the significant issues that
strongly impacts the strategic alliance and customer satisfaction.