Financial Analysis Management & Enterprise

This document provides an introduction to financial analysis management and enterprise. It covers topics such as the meaning of statistics, types and sources of data, contrast between population and sample, importance of statistical techniques in achieving business objectives, and the difference between descriptive and inferential statistics. It also includes examples of datasets and their application in statistical methods.

Financial Analysis Management
& Enterprise

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
PART 1............................................................................................................................................1
1. Meaning of statistics and its features......................................................................................1
2. Types and the sources of the data information which a business required to access..............2
3. Stating contrast between population and the sample..............................................................2
4. Importance of employing the statistical techniques in achieving business objectives............3
5. Explaining the difference between an inferential and descriptive statistics...........................4
6. Provide a relevant example of the dataset with application or employing of the statistical
methods with graph.....................................................................................................................5
Part 2................................................................................................................................................6
(1) Difference between descriptive and inferential data.............................................................6
(2) Descriptive statistics and inferential statistical data analysis................................................6
(3) Graphical analysis of data...................................................................................................12
CONCLUSION..............................................................................................................................13
REFERENCES..............................................................................................................................14

INTRODUCTION
PART 1
1. Meaning of statistics and its features
Statistics means an aggregate of the facts that is been affected to the marked extent
through various causes that is been expressed in numerical terms, estimated and enumerated in
accordance to the reasonable accuracy standards. The data under statistics are been collected in
the systematic manner for the particular purpose and are placed relating to each other (Parihar,
2018). In other words it is stated as the statement of the facts in numerical terms within the
department of an inquiry and seems as the most comprehensive subject that involves each and
every aspect of the statistics. Some of the characteristics of statistics are as follows-
Aggregate of the facts – A single number cannot be indicated as statistics, however,
aggregate of the wide range of data constitutes statistics. For instance- figures of exports, birth,
import etc. These figures are analysed relating to the place, frequency and time.
Numerically expressed – It does not include any type of statement that are been
expressed in qualitative elements. It takes into account only the quantitative statements such as
wheat production resulted as 20 thousand tonnes in the year 1990 as compared to 14 thousand
tonnes during 1985.
pre-determined purpose- The objective and the purpose of inquiry need to be clearly
stated prior to data collection. In statistics it is essential to define concrete and clear objective
terms with appropriate purpose of a inquiry.
systematic manner- A suitable plan must be framed in order to collect data and a work
needs to be carried in the systematic manner.
placed in place of each other- The quantitative data must be comparable, because
statistics are been gathered majorly with an an objective of comparison. For the purpose of
making valid and reliable conclusions, data needs to uniform and homogeneous.
Affected by various causes- Under statistics, numerical data are been affected by the
large number of the causes.
Estimated figures as per reasonable accuracy standards- statistical data might be
reflected either in a way of actual counting and by estimation. The data that are been gathered by
measurement and counting will be said as exact or accurate but estimated figures could not be
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seen as accurate and thus accuracy of an estimated value mainly depends on purpose and the
nature of an inquiry.
There are specifically two main techniques of statistics that is been counted as useful in
assessing the data (Sotirchos, Fitzgerald and Crainiceanu, 2019). It involves inferential that
provides for drawing appropriate conclusions from the data subjected to the random variation
and descriptive statistics that summarizes the data from the sample by making use of the indexes
like standard deviation, median, mean etc.
2. Types and the sources of the data information which a business required to access
The business organization could access mainly two types of the data that includes
primary and the secondary sources of collecting data. Primary data reflects the first-hand data
that is been gathered in direct connection with the respondent through personal investigation,
questionnaire etc. Such data tend to be pure and seen as original for a particular purpose (Sources
and type of data, 2017). On the other hand, secondary data are seen as just opposite to the
primary data as they are been gathered from the already available sources that is from the
published articles, book and journals. Such sources of the data are been used by surveyors fro
collecting the data and in conducting an analysis.
There are two main sources of the data that involves statistical and the non-statistical
sources. Statistical sources are the data that are been gathered for official purposes and involves
surveys that are conducted officially and also include censuses. Non-statistical sources means the
data that is been gathered for an administrative purposes fro private sector.
3. Stating contrast between population and the sample
Population Sample
Under this the measurable quality is referred in
terms of the parameter.
However, In sample, the quality measured is
been stated as the statistic.
It is been counted as the complete dataset for
analysing and drawing the conclusions on an
overall population.
It is considered as the part or subset of
population where as small portion of the
population is taken the data and it is been
assessed.
In this the reports are indicated as the true and
accurate representation of an opinion.
In sample, reports are having margin of the
error and the confidence interval.
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It is comprised of all the members in a
specified group.
It means the subset which represents an entire
population.
It involves complete enumeration of the items
under the statistical study.
It includes study of only the part of population
and not entire data.
Population is been seen as the specific interest
group.
Sample is choosing of the population from
which the data is been gathered.
Example- All the 5200 students had enrolled at
the GHC during 2011.
For instance- 28 GHC are been surveyed out of
total students fro assessing a particular area of
issue.
4. Importance of employing the statistical techniques in achieving business objectives
In a modern world, statistical methods are been universally applicable and are closely
connected with the human actions and the behaviour that helps in defining the human behaviour
on a practical basis (Ribeiro and et.al., 2017). Statistical methods plays an important role in the
business for achieving the objective are as follows-
Market research- An organization can make use of the statistics in the market research
and the development of the new product. Company could take the random surveys of the
participants for gauging acceptance of the market and the potential for the proposed product.
This analysis helps in constructing the break-even model for the purpose of identifying the sales
volume that is necessary for product in succeeding.
ROI- Statistical methods could allow the managers in evaluating project under the several
economic environments, strength of competition and the changing preferences of the consumer.
Forecasting- Through application of the statistical methods managers could be able
assess the past data for the purpose of finding the statistical trends and in making the prediction
about future. For instance- previous sales in relation to all the products sold could be made for
making the estimates about future volume sales under the particular economic conditions. In turn
such projections or anticipations are used for setting up the production schedules.
Performance measurement- The most common use of the statistics is measuring the
performance and the output of the production from an employee in order to find out that worker
meets desired standards of productivity.
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5. Explaining the difference between an inferential and descriptive statistics
Descriptive statistics- It refers to the discipline which provides a quantitative description
in relation to the significant characteristics of dataset. For describing the properties, it makes use
of the central tendency that is mean, mode , range, variance etc. Under this the data by the
scholar is been presented in a meaningful way with helps of the graphical and the numerical tools
like tables, graphs, charts etc. in accurate manner.
Inferential statistics- It relates to generalising the results from sample to population
which in turn means that results generated from the sample analysis could be deducted to the
larger population from which sample is been taken. It is been counted as the most convenient
way in drawing inferences about population. This tool is used for determining probability of the
properties of population based on properties of sample by way of employing the probability
theory.
Descriptive statistics Inferential statistics
It is the methods that mainly concerns with
describing population within study.
It is the type of the statistics that mainly focus
on drawing the conclusions about population
as based on observation and the sample
analysis (Difference between descriptive and
inferential statistics, 2018).
It gathers, organizes, presents and assess the
data in meaningful manner.
On the other side, inferential statistics makes
comparison of the data, test the hypotheses and
makes predictions relating to future outcomes.
In descriptive statistics, tabular representation
is been made of the final results.
However, in this final outcome is been
presented in form of the probability.
It describes for a particular situation. On the other side, inferential statistics depicts
likelihood regarding occurrence of an event.
This method explains the data that is been
already known in order to summarize the
sample.
Inferential statistics aims for reaching
conclusion for learning about population which
extends beyond availability of the data.
For example- Standard deviation, range, mean For instance- ANOVA, regression analysis
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etc. and hypotheses testing etc.
Thus, from the above analysis it could be reflected that descriptive statistics is about
illustrating current dataset while inferential focuses on making the assumption on an additional
population which is beyond dataset under the study. Moreover, descriptive statistics facilitates
summation of data where researcher makes a detailed study. However, inferential statistics
involves making of the generalisation that in turn means the data provided is not been analysed
properly.
6. Provide a relevant example of the dataset with application or employing of the statistical
methods with graph
Figure 1Netflix COGS as percentage of sales revenue
From chart given above it can be observed that in year 2015 and 2016 COGS as part of sales
revenue was 68% and 71% but then it declines to 63% which reflect that Netflix improve its
performance. Now firm have better control on its business expenses. This reflect that firm cost
control strategy is effective.
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Figure 2Net profit ratio of Amazon
Net profit ratio of Amazon increased from 1% to 4% which reflect that firm control its direct and
indirect business expenses. It can be said that firm successfully improve its business performing
by controlling expenses in the business.
Part 2
(1) Difference between descriptive and inferential data
There is big difference between descriptive and inferential data. Main purpose behind
preparing descriptive statistics is that it gives overview of the variables in terms of its average
value and way in which their values are fluctuating for particular period of time. On other hand,
inferential data reflect relationship between variables and impact that one has on another. It also
assists in estimating probability of happening of certain event if specific situation appears. Thus,
it can be said that descriptive statistics give basic overview of the variable but inferential
statistics help one in exploring ways in which two variables are connected to each other.
(2) Descriptive statistics and inferential statistical data analysis
Netflix Amazon
Mean 168.6 928.9
Mode #N/A #N/A
Median 123.6 779.5
SD 106.50 517.23
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Mean refers to the average of the value of the variable. In present case it can be observed that
average value of the Netflix share price is 168.6 which means that on an average share of the
Netflix valued at 168.6. On other hand, in case of Amazon mean value of the share price is
928.9. This indicate that share price is high in case of Amazon then Netflix. Median is another
tool that is usually used by the analyst to make decisions. It is the tool that classify entire data in
to two multiple parts equally. By comparing values above and below mean value variation in
trend can be identified. In case of Netflix median value is 123.6 and in case of Amazon median
value is 779.5. Standard deviation is another important descriptive analysis tool that is
commonly used by the analyst to analyse the variables. It can be observed that standard deviation
in case of Netflix is 106.50 and same in case of Amazon is 517.23. Thus, it can be said that
Amazon share price is deviating at higher rate then Netflix. Hence, risk is high in case of
Amazon then Netflix.
Netflix
Data Trend Netflix Forecast Netflix
01-02-2019 358.1
01-03-2019 356.6
01-04-2019 377.3 364.0
01-05-2019 364.0 366.0
01-06-2019 366.0 369.1
01-07-2019 369.1 366.4
01-08-2019 366.4 367.1
01-09-2019 367.1 367.5
01-10-2019 367.5 367.0
01-11-2019 367.0 367.2
01-12-2019 367.2 367.3
01-01-2020 367.3 367.2
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Amazon
Data Trend Amazon Forecast Amazon
01-02-2019 1639.8
01-03-2019 1780.8
01-04-2019 1887.3 1769.3
01-05-2019 1769.3 1812.5
01-06-2019 1812.5 1823.0
01-07-2019 1823.0 1801.6
01-08-2019 1801.6 1812.4
01-09-2019 1812.4 1812.3
01-10-2019 1812.3 1808.8
01-11-2019 1808.8 1811.1
01-12-2019 1811.1 1810.7
01-01-2020 1810.7 1810.2
In case of Netflix it is expected that trend will be in line to current performance. Hence, it
can be said that trend in share price seen currently will remain in future time period. On other
hand, in case of Amazon also similar trend is observed.
H0: Return on Netflix shares are not affected by NASDAQ return percentage
H1: Return on Netflix shares are affected by NASDAQ return percentage
SUMMARY OUTPUT
Regression Statistics
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Multiple R 0.959235
R Square 0.920133
Adjusted R
Square 0.918756
Standard Error 30.35722
Observations 60
ANOVA
df SS MS F
Significance
F
Regression 1 615791.1 615791.1 668.2046 1.6E-33
Residual 58 53450.53 921.5608
Total 59 669241.7
Coefficien
ts
Standar
d Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept -338.219 19.9931
-
16.9168
4.26E-
24
-
378.239
-
298.198
-
378.239
-
298.198
NASDA
Q-IXIC 0.086711
0.00335
4
25.8496
5
1.6E-
33
0.07999
6
0.09342
5
0.07999
6
0.09342
5
Interpretation
Multiple R value is 0.95 which reflect that there is strong correlation between variables. R
square value is 0.92 which reflect that model is efficiently explaining relationship between
dependent and independent variables. Value of level of significance is 1.6 which reflect that with
change in index performance any big variation is not observed in dependent variable value.
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Coefficient value 0.08 which means that with small change in NASDAQ 0.08-point change in
observed in Netflix share price. Null hypothesis accepted.
H0: Return on Amazon shares are not affected by NASDAQ return percentage
H1: Return on Amazon shares are affected by NASDAQ return percentage
Regression analysis (Amazon)
Summary output
Regression Statistics
Multiple R 0.970305
R Square 0.941492
Adjusted R
Square 0.940483
Standard Error 126.1845
Observations 60
ANOVA
df SS MS F
Significance
F
Regression 1 14860729 14860729 933.3144 1.91E-37
Residual 58 923506.9 15922.53
Total 59 15784236
Coefficien
ts
Standar
d Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept -1560.75
83.1044
6
-
18.7806
2.5E-
26 -1727.1 -1394.4 -1727.1 -1394.4
NASDA 0.425967 0.01394 30.5501 1.91E- 0.39805 0.45387 0.39805 0.45387
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Q-IXIC 3 9 37 7 7 7 7
Interpretation
Multiple R value is 0.97 which reflect that there is strong correlation between variables. R
square value is 0.94 which reflect that model is efficiently explaining relationship between
dependent and independent variables. Value of level of significance is 1.9 which reflect that with
change in index performance any big variation is not observed in dependent variable value.
Coefficient value 0.42 which means that with small change in NASDAQ 0.42-point change in
observed in Amazon share price. Null hypothesis accepted.
Table 1Correlation value
Correlation
Netflix 0.95
Amazon 0.97
From table given above it can be observed that correlation value in case of Netflix is 0.95 in
respect to revenue and net profit which means that both are changing at same rate. This also
mean that expenditures are made by Netflix as specific percentage of sales and due to this reason
revenue and net profit change at same rate. Same thing is observed in respect to Amazon as its
correlation value is 0.97.
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(3) Graphical analysis of data
Figure 3Amazon net profit
Figure 4Netflix net profit
It can be seen from above table that profitability of both firms increases on yearly basis.
Important point to note is that this increase happened constantly which reflect that Netflix and
Amazon are performing better. Higher jump in 2018 in net profit is observed in case of Amazon
then Netflix. This indicate that both firms maintain strict control on expenditures in the business.
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CONCLUSION
On basis of above discussion, it is concluded that there is significant importance of the
statistics because by using same firms easily measure their business performance and make
business decisions. There is huge difference between descriptive and inferential statistics but
both have huge importance for the firms at their own place. Hence, in can be said that managers
must use both methods to evaluate their performance.
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REFERENCES
Books and Journals
Parihar, S., 2018. Statistics for Management. South Asian Journal of Management. 25(2). pp.226-
229.
Ribeiro, V. and et.al., 2017, August. Importance of Statistics for Data Mining and Data Science.
In 2017 5th International Conference on Future Internet of Things and Cloud Workshops
(FiCloudW)(pp. 156-163). IEEE.
Sotirchos, E. S., Fitzgerald, K. C. and Crainiceanu, C. M., 2019. Reporting of R2 Statistics for
Mixed-Effects Regression Models. JAMA neurology. 76(4). pp.507-507.
Online
Difference between descriptive and inferential statistics. 2018. [Online]. Available
through:<https://keydifferences.com/difference-between-descriptive-and-inferential-
statistics.html>
Sources and type of data. 2017. [Online]. Available
through:<https://www.toppr.com/guides/economics/collection-of-data/source-and-
collection/>
. [Online]. Available through:<>
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