Data Handling and Decision Making: Assignment

DATA HANDLING AND
DECISION MAKING

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
QUESTION .....................................................................................................................................1
Statement of specific decision Barclays required to make..........................................................1
Descripting of relevant information used for analysis.................................................................4
a. Discussion of information related to business with representation of dataset.........................4
b. Obtaining of dataset with appropriate explanation..................................................................5
c. Importance of this statement in decision making process of business entity...........................5
Analysing the data mining procedures from data set...................................................................6
Data preparation, cleaning and filtering.......................................................................................6
Implicating the descriptive data analysis effective for immediate observation for business
performance.................................................................................................................................6
Developing organisational forecasting report............................................................................25
Visualisation and interpretation of outcomes............................................................................26
Decision making recommendations...........................................................................................26
CONCLUSION..............................................................................................................................26
REFERENCES..............................................................................................................................27

INTRODUCTION
Data handling is the techniques of collecting the data and managing it in the books of accounts which will be adequate and
effective with respect to make appropriate analysis over firm’s performance. To implicate the reformative changes in the operations of
Barclays which reflect in potential growth of this banking industry. The company have been operating in UK with facilitating the
internal banking services which is comprised of various activities such as Corporate banking, personal banking, investment
management and wealth management. In the present assessment there will be determination of the facts which are affecting the growth
of industry. The analysis will be based on analysing impacts of profitability on the amount of funds derived through shareholders.
Thus, the profitability of this banking industry will affect the number of investors in each period. It will be consisting influences of
statistical tools to analyse the relationship between variables.
QUESTION
Statement of specific decision Barclays required to make
The operational performance of Barclays Plc analysed through measuring the consequences which affects the number of
shareholders to the organisation. To analyse such variations there will be collection of reliable information which have been gathered
from past 5 year’s performance of the organisation. The data is gathered through annual reports of the company. Income statement and
balance sheets are some major sources for gathering information regarding firm's financial performance of the company. It is
consisting of profits as well as revenue derived from operations. Along with this, there will be collection of details relevant with the
number of shareholder’s to be collected to analyse the information. The net income of organization contributes significant aspect for
identifying shareholder's equity. The net income is calculated by considering its revenues for specified duration and excluded the cost
of goods sold. The COGS consider all expenses which are used for operating business like payroll, advertising, rent, taxes and
equipment. In the similar aspect, shareholder's equity is liabilities which are excluded from its business assets as it is listed on
organization's balance sheet. It contributes to assets of company and impact the book value or shareholder's equity. If profit is
generated and with retention of portion of margin after excluding each cost where equity of owner generally increases. On the contrary
1

aspect, if profit is generated but its cost of performing business has been exceeded with profit and then shareholder's equity has
decreased on usual aspect (Cole and Sokolyk, 2018). However, net income is referred as one individual factor which impact
shareholder's equity in business entity. Furthermore, net income is referred as one factor which impact shareholder's equity as it could
also raise with business owner investing more money within business. Simultaneously, it could decrease if owner took money out
from business.
2

In the similar aspect, there is evaluation of this issue with context of Barclay's bank where shareholder's equity is increasing
from huge proportion but in 2017 it has slight decrements. Conversely, its net profit is having various ups and down so profitability
negative impact in 2017 is also reducing its stakeholder’s equity. In short, it had been derived that stockholder’s equity will also move
in similar position to its net income and paid dividend also contributes in this movement. This company not always make money as it
has created negative income which is replicated as net loss which is impacting stakeholder which is opposing direction ( The
Relationship Between Net Income & Owner's Equity, 2018).
From year 2015 it had not involved in merger, acquisition or restructuring till year 2017. Simultaneously, from year 2016 to
2017, its expenses were increasing along with provision for taxes and extraordinary items had increased with huge proportion. Thus,
owner's equity had raises when business entity will produce margin and retain part after payment of dividends. Losses will lead to
3

decreasing this equity and owner could put additional cash for continuing its operations and sell off surplus assets for raising cash and
to liquidate its assets or to keep appropriate track of its expenses for increasing net income along with shareholder's equity.
In respect with the operational performance of the Barclays on which there have been use of 5 years of financial information
which will be measured to analyses the firm’s performance in this respective period. Thus, it must be said that there is requirement of
making operating changes which will help and govern the professionals in reducing the costs implicated in the operations.
Data integrity:
All data regarding Barclays plc is collected through audited financial reports or audited annual reports of the company. In this
regard, it can be said that the report contains data integrity, as the audited annual reports provides more reliable information than an
non audited financial reports.
Descripting of relevant information used for analysis
a. Discussion of information related to business with representation of dataset
Year
Interest
income
Interest
expenses
Net
interest
income
Non
interest
revenue
Net
revenue
Net
operating
income
Stockhold
er's equity
2013 18315 6715 11600 16844 28444 540 55385
2014 17363 5283 12080 13688 25768 -174 59567
2015 17201 4643 12558 13426 25984 -394 59810
2016 14541 4004 10537 10914 21451 1623 64873
2017 13631 3786 9845 11231 21076 -1922 63905
The main business of Barclay bank is for managing spread among deposits which is paid to consumer at particular rate which
had been gained from loans. In simple words, interest which had been earned by bank through loans is higher from interests which is
4

paid on deposits, it produces income through spread of interest rate (Barclays PLC, 2018). In the same series, non interest revenue is
creditor or bank income which is derived through initial fees which considers transaction and deposit fees, annual fees, inactivity fees,
NSF or insufficient funds, deposit and check slip fees. The credit card issuers will also charge penalty fees as it considers over the
limit and late fees (Lestari and Riyadi, 2018).
In this dataset, net operating income is used with objective of analysing investments of real estate which produces income. It is
equalised to revenue as it is prior to tax figure which is excluding interest and principal payments on loans, depreciation, amortization
and expenditures. Furthermore, stockholder's equity is amount of capital specified in business with its shareholders along with donated
earnings and capital generated through operation of business, excluding any issued dividends. Simultaneously, this dataset is for
evaluation from year 2013 to 2017. There is consideration of interest income, interest expense, non interest income, non interest
revenue, net operating income and shareholder's equity.
b. Obtaining of dataset with appropriate explanation
In this evaluation the data set has considered net interest income, stockholder's equity and non-operating income which had
been extracted from annual report of Barclay bank. In this aspect, net interest income has been extracted by excluding interest expense
from interest income. Net revenue is generated with combination of net interest income and noninterest revenue and in the same
series, there is mentioning of net operating income and shareholder's equity which is obtained from statement of profit and loss and
statement of financial position respectively from its consecutive past 5 years of annual report (Le and et.al., 2018).
The data is being gathered through audited financial reports of the Barclay bank. In addition, data has also been gathered
through some books and journals and articles based on the Barclay bank. Furthermore, statistical data of Government, several
magazines are also been used for collecting financial data of Barclay bank.
c. Importance of this statement in decision making process of business entity
The relationship of net income and stockholder's equity as it plays huge contribution with context of financial modelling and
helps top management related to dividend payments which any business entity periodically sent to its investors. It will be used for
5

maximising business value and to increase its impact on profit or margin. It is major tool which could be used for investing
perspective as it is extremely varied which is highly dependent on method of any individual organization. It is organised with
company perspective and pertained to ownership, preferred stock, paid in capital and for increment or diluting over time and
explanation about alteration in shareholder's equity.
In the same series, it will also help in gaining financial performance, position and for peer comparison as well along with
getting rough idea about dividends. In nutshell, it has been elaborated that for assisting in better decision making this relationship
helps majorly to investors, creditors and lenders. With perspective of investors, it performs fiscal analysis as basis of decision making
to invest or not whereas lending institutions will be examining financial health and confirms with presence of capacity for servicing
debt. This will help creditor as well, vendors with extension of credit might use this relationship for assessing credit worthiness of
business (Graham and Lin, 2018).
Analysing the data mining procedures from data set
Data preparation, cleaning and filtering
In respect with analysing the relationship between the profitability and number of shareholders to the firm there have been use of
various information such as Net income, operating income and shareholder equity of Barclays from 2013 to 2017 (Roth, 2018).
Implicating the descriptive data analysis effective for immediate observation for business performance
Descriptive analysis
Interes
t
income
Interes
t
expen
ses
Net
interes
t
income
Non
-interest
revenu
e
Net
revenue
Net
Operatin
g
income
Stockholder'
s
equity
Mean 1621 Mean 4886 Mean 1132 Mean 1322 Mean 24544. Mean -65.4 Mean 60708
6

0.2 .2 4 0.6 6
Standa
rd
Error
899.
42
Standa
rd
Error
526.
77
Standa
rd
Error
498.
86
Standar
d
Error
1064.
63
Standar
d
Error
1420.8
3509
Standard
Error
582.4
06
Standard
Error
1703.
095
Media
n
1720
1
Media
n 4643
Media
n
1160
0 Median
1342
6 Median 25768 Median -174 Median 59810
Mode
#N/
A Mode
#N/
A Mode
#N/
A Mode #N/A Mode #N/A Mode #N/A Mode #N/A
Standa
rd
Deviati
on
2011
.18
Standa
rd
Deviat
ion
1177
.9
Standa
rd
Deviat
ion
1115
.49
Standar
d
Deviati
on
2380.
58
Standar
d
Deviati
on
3177.0
8385
Standard
Deviation
1302.
3
Standard
Deviation
3808.
236
Sampl
e
Varian
ce
4044
829
Sampl
e
Varia
nce
1387
456
Sampl
e
Varian
ce
1244
320
Sample
Varianc
e
5667
148
Sample
Varianc
e
10093
861.8
Sample
Variance
1695
985
Sample
Variance
14502
662
Kurtos
is -2.32
Kurtos
is
0.62
642
Kurtos
is -1.69
Kurtosi
s
0.422
34
Kurtosi
s
-
2.1837
497 Kurtosis
0.758
51 Kurtosis
-
0.805
43
Skewn
ess -0.51
Skewn
ess 1.06
Skewn
ess -0.42
Skewne
ss
0.850
4
Skewne
ss
-
0.0939
807 Skewness
-
0.264
4 Skewness
-
0.362
93
Range 4684 Range 2929 Range 2713 Range 5930 Range 7368 Range 3545 Range 9488
Minim
um
1363
1
Minim
um 3786
Minim
um 9845
Minimu
m
1091
4
Minimu
m 21076
Minimu
m -1922 Minimum 55385
Maxim
um
1831
5
Maxim
um 6715
Maxim
um
1255
8
Maxim
um
1684
4
Maxim
um 28444
Maximu
m 1623 Maximum 64873
Sum
8105
1 Sum
2443
1 Sum
5662
0 Sum
6610
3 Sum
12272
3 Sum -327 Sum
30354
0
Count 5 Count 5 Count 5 Count 5 Count 5 Count 5 Count 5
Larges
t
(1)
1831
5
Larges
t
(1) 6715
Larges
t
(1)
1255
8
Largest
(1)
1684
4
Largest
(1) 28444
Largest
(1) 1623
Largest
(1) 64873
7

Smalle
st
(1)
1363
1
Smalle
st
(1) 3786
Smalle
st
(1) 9845
Smalles
t
(1)
1091
4
Smalles
t
(1) 21076
Smallest
(1) -1922
Smallest
(1) 55385
Confid
ence
Level
(95.0%
)
2497
.2
Confid
ence
Level
(95.0%
)
1462
.56
Confid
ence
Level
(95.0%
)
1385
.06
Confide
nce
Level
(95.0%)
2955.
88
Confide
nce
Level
(95.0%
)
3944.8
7064
Confiden
ce
Level
(95.0%)
1617.
02
Confidence
Level
(95.0%)
4728.
55
Interpretation: On the basis of above listed descriptive analysis on which there have been use of various details and
ascertainment of statistical outcomes. Thus, the mean value of all the data which have been considered by researcher in this process
that defines results of revenue, profits and equity balance of the organisation. In analysing the outcomes on which it can be said that
there has been implication of various techniques which in turn will be useful and effective to have demonstration over the use of
techniques for growth planning and analysing the level of investors associated with the business. Therefore, the mean value of
variables which have been used by professionals such as revenue generated through interest by Barclays were average at 1621.02,
Interest expenses were 4886.2 respectively.
Therefore, such outcomes have represented that the net income through interest were 11324. Along with this, in analysing the
non-interest income of this banking industry which have presented the outcomes as 13220.6 which have present the net revenue of the
firm as 24544.6. In analysing the operating income of the organisation there have been determination of higher operating expenses
which have been incurred by industries were comparatively higher (3 Ways Big Data Can Influence Decision-Making for
Organizations, 2018). Thus, due to such impacts there have been reduction in the operating income of the business which is reflecting
the negative outcomes. Moreover, in respect with analysing the mean value of operating income which is -65.4. In analysing the
average value of shareholders of the firm in respective 5 years of period which have been determined as 60708.
Correlation analysis:
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This is statistical techniques which have been used to determine the relationship between two or more variables. This will be
effective techniques which in turn will be useful for analysing the appropriate outcomes through demonstrating the similarities
between the variables which have been used (Barclays PLC, 2018).
Net interest income on stockholder’s equity
Hypothesis
H0: There is no mean significance relationship between net interest income and stockholders
H1: There is a mean significance relationship between net interest income and stockholders
Descriptive Statistics
Mean Std.
Deviation
N
Net interest
income 11324.00 1115.491 5
Stockholder's
equity 60708.00 3808.236 5
Correlations
Net interest
income
Stockholder's
equity
Net interest
income
Pearson Correlation 1 -.674
Sig. (2-tailed) .213
Sum of Squares and
Cross-products 4977278.000 -
11446094.000
Covariance 1244319.500 -2861523.500
N 5 5
9

Stockholder's
equity
Pearson Correlation -.674 1
Sig. (2-tailed) .213
Sum of Squares and
Cross-products
-
11446094.00
0
58010648.000
Covariance -2861523.500 14502662.000
N 5 5
Interpretation: On the basis of analyzing the correlation among the net interest income and stockholders of the organisation.
The outcomes represented the negative results which in turn presenting that, there have been negative relationship between variables.
The level of defining relationship between the variables in -1 to +1. In accordance with these outcomes on which there have been
negative relationship among the variables. -0.674 proves the null hypothesis which defines that, there is no mean significance
relationship between net interest income and stockholders.
Non-interest income and stockholder
H0: There is no mean significance relationship between non-interest income and stockholders
H1: There is a mean significance relationship between non-interest income and stockholders
Descriptive Statistics
Mean Std.
Deviation
N
Stockholder's
equity 60708.00 3808.236 5
Non-interest
revenue 13220.60 2380.577 5
10

Correlations
Stockholder's
equity
Noninterest
revenue
Stockholder's
equity
Pearson Correlation 1 -.992**
Sig. (2-tailed) .001
Sum of Squares and
Cross-products
58010648.00
0
-
35972851.000
Covariance 14502662.00
0 -8993212.750
N 5 5
Non interest
revenue
Pearson Correlation -.992** 1
Sig. (2-tailed) .001
Sum of Squares and
Cross-products
-
35972851.00
0
22668591.200
Covariance -8993212.750 5667147.800
N 5 5
**. Correlation is significant at the 0.01 level (2-tailed).
Interpretation: By considering the above analysed correlations among the variables on which it can be said that there has
determination of the relationship among the non-interest income and stockholders. Thus, in demonstrating the outcomes on which
there have been negative outcome which were derived from the analysis. Thus, it is comparatively lower than the ideal range of
correlation such as +-1 to +1. Moreover, -0.992 have been demonstrated as comparatively negative that, there will be acceptance to the
null hypothesis, there is no mean significance relationship between non-interest income and stockholders.
11

Net operating income and stockholders
H0: There is no mean significance relationship between Net operating income and stockholders
H1: There is a mean significance relationship between Net operating income and stockholders
Descriptive Statistics
Mean Std.
Deviation
N
Stockholder's
equity 60708.00 3808.236 5
Net income -65.40 1302.300 5
Correlations
Stockholder's
equity
Net income
Stockholder's
equity
Pearson Correlation 1 -.086
Sig. (2-tailed) .891
Sum of Squares and
Cross-products
58010648.00
0 -1706913.000
Covariance 14502662.00
0 -426728.250
N 5 5
Net income Pearson Correlation -.086 1
Sig. (2-tailed) .891
12

Sum of Squares and
Cross-products -1706913.000 6783939.200
Covariance -426728.250 1695984.800
N 5 5
Interpretation: In relation with above listed correlation analysis which have identifies the relationship between the net
operating income and stockholder of the organisation. Thus, in outcomes were between the level of correlation such as -1 to +1 which
is -0.086. Therefore, there is negative relationship between the variables on which it can be said there will be acceptance to the
alternative hypothesis. Thus, it defines that, there is a mean significance relationship between Net operating income and stockholder.
Moreover, the rise in operating income will affect the number of shareholders to the firm.
Net revenue and stockholders
H0: There is no mean significance relationship between Net revenue and stockholders
H1: There is a mean significance relationship between Net revenue and stockholders
Descriptive Statistics
Mean Std.
Deviation
N
Stockholder's
equity 60708.00 3808.236 5
Net revenue 24544.60 3177.084 5
Correlations
13

Stockholder's
equity
Net revenue
Stockholder's
equity
Pearson Correlation 1 -.980**
Sig. (2-tailed) .003
Sum of Squares and
Cross-products
58010648.00
0
-
47418945.000
Covariance 14502662.00
0
-
11854736.250
N 5 5
Net revenue
Pearson Correlation -.980** 1
Sig. (2-tailed) .003
Sum of Squares and
Cross-products
-
47418945.00
0
40375447.200
Covariance
-
11854736.25
0
10093861.800
N 5 5
**. Correlation is significant at the 0.01 level (2-tailed).
Interpretation: In context with above derived outcome from the correlation analysis on the net revenue and stockholder of
Barclays which have presented the outcomes comparatively less than the correlation level. Thus, -0.980 defines acceptance to the null
hypothesis, that is there is no mean significance relationship between Net revenue and stockholders.
Regression analysis:
This statistical technique has been used by researchers in relation with identifying the relationship between the variables which
have been used to analyse their impacts and dependency on each other (Al-Hawari, Mumani and Momani, 2014). However, there will
14

be evaluation of the data set which will be adequate and effective in trims of meeting the requirements at the right time. Barclays
shareholder amount have been based on profitability of the organisation.
Net interest income and stockholders
H0: There is no mean significance relationship between Net interest income and stockholders
H1: There is a mean significance relationship between Net interest income and stockholders
Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
R Square
Change
F Change df1 df2 Sig. F Change
1 .674a .454 .272 3250.047 .454 2.492 1 3 .213
a. Predictors: (Constant), Net interest incom
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1
Regression 26322232.324 1 26322232.324 2.492 .213b
Residual 31688415.676 3 10562805.225
Total 58010648.000 4
a. Dependent Variable: Stockholder's equity
b. Predictors: (Constant), Net interest income
15

Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig. 95.0% Confidence Interval for
B
B Std. Error Beta Lower Bound Upper Bound
1
(Constant) 86749.456 16560.472 5.238 .014 34046.642 139452.271
Net interest
income -2.300 1.457 -.674 -1.579 .213 -6.936 2.336
a. Dependent Variable: Stockholder's equity
Coefficient Correlationsa
Model Net interest
income
1
Correlations Net interest
income 1.000
Covariances Net interest
income 2.122
a. Dependent Variable: Stockholder's equity
Interpretation: In analysing the regression analyses over the dependent variable shareholder’s equity and independent
variable as net interest income of Barclays there have been identification of the various information. However, in analysing the
outcomes on which there have been ascertainment of various data. Thus, in the model summary of the variables which represent the R
value as 0.674 while R square as 0.454. Therefore, it represents that there is 45.4% of relationship among the variables. Along with
this, as per analysing the significant value of the data base which have presented as 0.213 that is comparatively higher than the P value
16

of 0.05. Thus, it defines rejection to alternative hypothesis as, there is no mean significance relationship between Net interest income
and stockholders.
Non-interest income and stockholders
H0: There is no mean significance relationship between Non-interest income and stockholders
H1: There is a mean significance relationship between Non-interest income and stockholders
Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
R Square
Change
F Change df1 df2 Sig. F Change
1 .992a .984 .979 555.347 .984 185.096 1 3 .001
a. Predictors: (Constant), Non interest revenue
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1
Regression 57085418.218 1 57085418.218 185.096 .001b
Residual 925229.782 3 308409.927
Total 58010648.000 4
a. Dependent Variable: Stockholder's equity
b. Predictors: (Constant), Non interest revenue
17

Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig. 95.0% Confidence Interval for
B
B Std. Error Beta Lower Bound Upper Bound
1 (Constant) 81687.807 1561.938 52.299 .000 76717.023 86658.592
Non interest revenue -1.587 .117 -.992 -13.605 .001 -1.958 -1.216
a. Dependent Variable: Stockholder's equity
Coefficient Correlationsa
Model Non interest
revenue
1 Correlations Non interest revenue 1.000
Covariances Non interest revenue .014
a. Dependent Variable: Stockholder's equity
Interpretation: Determining the regression analysis over the non-interest income and stockholders of the organisation on
which outcomes have been determined by the researchers. Thus, in respect with the model summary of the data base which have
represented that R value as 0.992 and R square as 0.984. Thus, it can be said that there is 98.4% of relationship have been developed
among the variables. Thus, the changes in Non-interested income will be helpful in terms of generating the investors to Barclays.
Along with this, in analysing the significance value of the data base which have represented the value as 0.001 which is less than the p
value of 0.05. Thus, due to such outcomes on which there will be acceptance to the alternative hypothesis as, there is a mean
18

significance relationship between Non-interest income and stockholders. Moreover, this profitability analysis has the relationship with
the changes incurred in the stockholders on organisation. Moreover, there is need to increase the revenue through non-interest
activities in bank.
Net revenue and stockholders:
H0: There is no mean significance relationship between Net revenue and stockholders
H1: There is a mean significance relationship between Net revenue and stockholders
Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
R Square
Change
F Change df1 df2 Sig. F Change
1 .980a .960 .947 879.293 .960 72.031 1 3 .003
a. Predictors: (Constant), Net revenue
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1
Regression 55691181.172 1 55691181.172 72.031 .003b
Residual 2319466.828 3 773155.609
Total 58010648.000 4
a. Dependent Variable: Stockholder's equity
b. Predictors: (Constant), Net revenue
19

Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig. 95.0% Confidence Interval for
B
B Std. Error Beta Lower Bound Upper Bound
1 (Constant) 89534.406 3419.181 26.186 .000 78653.047 100415.765
Net revenue -1.174 .138 -.980 -8.487 .003 -1.615 -.734
a. Dependent Variable: Stockholder's equity
Coefficient Correlationsa
Model Net revenue
1 Correlations Net revenue 1.000
Covariances Net revenue .019
a. Dependent Variable: Stockholder's equity
Interpretation: As per analysing the relationship between the net revenue of Barclays with its amount of equity for respective
5 years there have been use of regression tool. Thus, in analysing the outcomes on which R value have been defined as 0.980 and R
square as 0.960. Thus, in respect with such outcomes on which it can be said that there is 96.0% relationship among the variables. In
analysing the significance value of the data base which is less than 0.05 such as 0.003. Thus, there is a mean significance relationship
between Net revenue and stockholders.
20

Net operating income and stockholders
H0: There is no mean significance relationship between Net operating income and stockholders
H1: There is a mean significance relationship between Net operating income and stockholders
Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
R Square
Change
F Change df1 df2 Sig. F Change
1 .086a .007 -.323 4381.064 .007 .022 1 3 .891
a. Predictors: (Constant), Net income
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1
Regression 429477.904 1 429477.904 .022 .891b
Residual 57581170.096 3 19193723.365
Total 58010648.000 4
a. Dependent Variable: Stockholder's equity
b. Predictors: (Constant), Net income
Coefficientsa
21

Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig. 95.0% Confidence Interval for
B
B Std. Error Beta Lower Bound Upper Bound
1 (Constant) 60691.545 1962.357 30.928 .000 54446.448 66936.641
Net income -.252 1.682 -.086 -.150 .891 -5.605 5.101
a. Dependent Variable: Stockholder's equity
Coefficient Correlationsa
Model Net income
1 Correlations Net income 1.000
Covariances Net income 2.829
a. Dependent Variable: Stockholder's equity
Interpretation: In accordance with analysing the data base which have presented that the R value as 0.086 and R square as
0.007 that defines there is 0.7% of relation is between operating income and shareholders. Thus, the significant value is 0.891 which is
more than 0.05. Thus, in respect with such outcomes on which it can be said that, there is no mean significance relationship between
Net operating income and stockholders.
As the correlation between these two data has been calculated as 1, it can be said that there is a perfect positive relation
between them.
22

Barclay’s revenue:
23

Profitability of Barclay:
24

Stockholder’s equity:
Developing organisational forecasting report
In respect with analysing the outcomes of shareholders and income of Barclays which have represented that there has been
positive relationship among the variables (Altuntas and Selim, 2012). Thus, it can be estimated that in the coming period there will be
growth in the equity share capital of industry. Thus, there is requirement of managing the operating expense of the organisation on
which the professionals will have positive outcomes through such operations.
Applicating machine learning techniques
To analysing the relationship among the variables there have been implication of various techniques which will be helpful in
determining the accurate outcomes (Amaral, 2013). Thus, there will be influences of regression, correlation, Anova and descriptive
statistics of the data base.
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Visualisation and interpretation of outcomes
As per analysing the outcomes of the above anlsyed data base which have represented that there is relationship between the
profitability of the organisation and number stockholders to firm (Bozorgi, Abedzadeh and Zeinali, 2015). It is basically due to the
reason that if Barclay is having appropriate profits art the end of period than there will be adequate number of investors to the firm.
There will be raise in the capital structure as the number of investors are interested in making fruitful investment in the business
(Intezari and Gressel, 2017).
Ethical and protection assurance
All sources used for data collection process is reliable and has been taken from valid sources such as company's audited
financial reports. No unauthorised source has been used which could have possibly manipulated the data and findings.
Decision making recommendations
As per defining the outcomes of the firm there is requirement of making adequate decisions which will help the in improving the
profitability of the organisation as well as mitigating the financial risks of firm. Thus, there are several recommendations which will
be helpful to Barclays Plc that will be helpful in managing the financial operations of the industry.
 Managing the operating expenses such as determining alternatives to reduce the costs.
 Improving banking services for better interest income generation
 Developing dividend policies for investors which will be effective in bringing them appropriate returns.
CONCLUSION
On the basis of above report on which it has been determined that there have been use of various statistical information which will
be adequate in terms of analysing the relations hip between the profitability and shareholder capital of Barclays Plc. Thus, it had been
determined that there is a relationship among the variables on which mitigating such risks will b helpful in analysing the outcomes.
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