Analysis of Statistical Methods for Business Decision Making

This report provides a comprehensive overview of statistics, its key characteristics, and various methods used in business. It begins with an introduction to statistics, explaining its role in analyzing numerical data for decision-making. The report then explores different sources and types of business information, differentiating between samples and populations. It highlights the value of statistical methods, distinguishing between descriptive and inferential statistics. A significant portion of the report is dedicated to evaluating descriptive and inferential statistics using real-world data, including a comparative analysis of Netflix and Amazon's share prices, along with graphical and numerical presentations. The report concludes by emphasizing the importance of statistical methods in strategic planning and achieving a competitive edge in business. References to relevant literature are also provided.

STATISTICS FOR
MANAGEMENT

Table of Content
 Introduction
 Introduction to statistics
 Sources and type of information businesses can access
 Difference among sample and a population
 Value of employing statistical methods
 Difference among inferential and descriptive statistics
 Evaluation of range of descriptive and inferential statistics
 Findings
 Conclusion
 References

Introduction
Statistical is a branch of analysing the numerical figures and assumptions
in order to get possible solutions against the business challenges.
There are types of statistical analysis methods are being used by
organisations in order to get the required results and to assist the
decision-making process. The report contains two sections as Part 1
and Part 2. The report presents the understating of statistics and its
key characteristics with its key statistical methods.

Introduction to statistics
Different perspectives are given by authors regarding the nature of
statistics. As per German author Gottfried Achenwall (1749), the
evaluation of data subject to a state or any significant state of
science is recognised as statistics. Earlier the statistics were used as
a method of collecting the data of population of a country. Earlier
the statistics were used as a method of collecting the data of
population of a country. It is recognised that the information
collected through population is collected through public provide an
estimation of strength and data subject to material prosperity of
other country.

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Key characteristic of statistics are defined as follows;
Exaggerated to a marked extent by various factors: In general,
statistical facts and statistics cannot be attributed to a specific cause.
A variety of factors operating collectively influence them to a
significant extent.
Sufficient to place in relation to each other: Numbers can be put in
contrast to one another.

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Overview of statistical method
Type of statistical methods are defined as follows;
Descriptive
Analytical method
Inductive method
 Inferential method
Applied methods

Sources and type of information
businesses can access
Information or data can be collected from various sources, but only few
sources remain workable in the context of statistical analysis and
control. There is type of data an organisations use for the purpose
of evaluation purpose. The data can be divided as follows;
 Internal data
 External data
 Qualitative data
 Quantities data

Difference among sample and a
population
In statistical terms the data can be measured in combine or separate
way. The size of data is divided in two form as “population” data set
and “sample” data set in statistical evaluation and differentiating
different size of data essential in order to get accurate results. A
population data set indicates towards the data of combined groups
with complete figures for instance the data of share price of different
companies is recognised as population data set.

Value of employing statistical methods
It is acknowledged that the value of statistical measures is quite crucial
for business entities subject to take future decisions and making a
sensible understanding towards future aims and objectives. The use
of different type of statistical measures helps in ascertaining the
desirable aim and objectives of organisation for sustainable future.

Difference among inferential and
descriptive statistics
Empirical and inferential statistics are seen as two separate sections of
statistics that serve to gather data, interpret results for interpretation,
but with various objectives. When, as expected, the analysis is
focused on linear regressions and descriptive statistics, it is very
difficult to identify these two forms of statistics. As the elements,
descriptive statistics are someone who determines the culture.

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Difference between inferential statistics and descriptive statistics
Basis of comparison Inferential statistics Descriptive statistics
Meaning The evaluation of convenient
group rather than sample groups
is considered as inferential
statistics.
Succinct the data in graphical
form is considered as descriptive
statistics.
Selection of data The data is collected form a
sample that creates inferences
subject to big number of
population and sample. It
generalise the population and
reflects the population.
The data is taken form specific
set of observations. The data
mainly indicates towards
recoding the data with clear
assessment of observations.
Use Inferential statistics is used to
explain population through
conclusive format and reflection.
The key use of descriptive
statistics mainly used to define
the information of sample in
graphical and presentation form.

Evaluation of range of descriptive and
inferential statistics
In this section the data relating to the monthly adjusted share price of
Netflix and Amazon for five years is taken in consideration for
descriptive and inferential analysis purpose. The main objective of
the statistical analysis is to compare the competitive edge among
Netflix and Amazon. The data of NASDAQ’s is taken as a base for
both the organisation.

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Descriptive analysis of share price of Netflix and amazon
Netflix Amazon
Mean 168.5693341 Mean 928.8533315
Standard Error 13.74959344 Standard Error 66.77442344
Median 123.5650025 Median 779.48999
Mode #N/A Mode #N/A
Standard Deviation 106.5038928 Standard Deviation 517.2324599
Sample Variance 11343.07919 Sample Variance 267529.4176
Kurtosis -0.722238298 Kurtosis -0.888356577
Skewness 0.845531012 Skewness 0.610254357
Range 342.628563 Range 1707.24997
Minimum 48.80143 Minimum 305.459991
Maximum 391.429993 Maximum 2012.709961
Sum 10114.16004 Sum 55731.19989
Count 60 Count 60
Largest(1) 391.429993 Largest(1) 2012.709961

Findings
Graphical presentation of Netflix

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Graphical presentation of Amazon

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Inferential analysis
The financial information of Netflix and Amazon is taken in
consideration subject to inferential analysis. The sample of net profit
of both the organisations is
Net profit Amazon Netflix
2015 123 596
2016 187 2371
2017 559 3033
2018 1211 10073

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The sample of revenue of the chosen organisation is analysed below in
order to understand the interrelation among the evaluation.
Poi
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4 1211 1 100.
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3 559 2 66.6
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3 3033 2 66.6
0%
2 187 3 33.3
0%
2 2371 3 33.3
0%
1 123 4 0.00
%
1 596 4 0.00
%

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Revenues Amazon Netflix
2015 232887 15794
2016 177866 11693
2017 135987 8831
2018 107006 6780

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4 2018 1 100.
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1 232
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1 15
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3 2017 2 66.6
0%
2 177
866
2 66.6
0%
2 11
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2 2016 3 33.3
0%
3 135
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3 33.3
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3 88
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0%
1 2015 4 0.00
%
4 107
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4 0.00
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4 67
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4 0.00
%

Conclusion
The above report clearly defines the meaning of statistics with its key
characteristic and it is quite cleared that statistical methods play a
vital role in terms of decision making and strategic planning. The
source of data and information from different business are
undertaken with sample and a population. The overview of
statistical measures presents that the figures and outcomes assist in
attaining the competitive edge for an organisation.

References
 Mertler, C.A. and Reinhart, R.V., 2016./Advanced and
multivariate statistical methods: Practical application and
interpretation/. Routledge.
 Hopkins, W.G. and Batterham, A.M., 2016. Error rates, decisive
outcomes and publication bias with several inferential
methods./Sports Medicine/,/46/(10), pp.1563-1573.

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