Statistics for Management: A Report on Samsung's Business Strategies

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Added on  2023/01/19

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This report provides an overview of statistics for management, focusing on data collection, analysis, and interpretation. It defines key statistical concepts, including descriptive and inferential statistics, and explores various statistical methods like mean, correlation, and regression. The report also differentiates between primary and secondary data, samples, and populations. A significant portion of the report analyzes Samsung's business, highlighting the value of statistical methods in making informed decisions related to finance, marketing, and overall business performance. It includes key findings using regression analysis for Microsoft and Apple. The report emphasizes the importance of systematic data collection and the use of statistical tools to gain a competitive advantage in the electronic business market. The report concludes by showcasing the practical application of statistical techniques to improve business strategies and performance, using Samsung as a case study.
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Statistics for
Management
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Cover Content
Introduction
Definition of Statistics
Key characteristics of Statistics
Overview of statistical methods
Types of data
Sources of data
Difference between a sample and a population
Value of statistical methods
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Cover Content
Difference between Differential and Inferential Statistics
Key findings
References
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INTRODUCTION
Statistics refers to a mathematical science, that pertains to collect,
organise, analyse and interpret a data. It provides a number of tools to
predict and forecast a data to organisation, that helps in taking
important decisions regarding with finance, marketing and other
services.
The present report is going to collect an in-depth knowledge of
statistical management, including its usage in resolving the business
challenges. Samsung is chosen for this analysis, that deals in electronic
products, as designer, manufacturer and distributor in UK.
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Definition of Statistics
Statistics can be defined as a tool to collect, analyse and interpret the
large numerical data, by using a number of methodologies . It
includes index, correlation and regression, trend forecasting and
more, which are majorly classified into two forms of statistics as
inferential and descriptive. According to Prof. Bowley, statistics can
be defined as a branch of mathematics that mainly deal with
counting and interpreting a numerical information.
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Key characteristics of Statistics
Statistics are aggregate of facts: Information that is collected by
statistical methods never includes the single or isolated figures,
because such data cannot be compared, to drawn specific
conclusion. Therefore, statistical data is aggregate of facts, that are
capable to offer meaningful information.
Statistical information must be collected in systematic manner: To take
business decisions or draw a valid conclusion, data must be gathered
systematically, by following a suitable plan
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Data must be expressed in numerical form: As statistical methods can
only be applied on information which is numerically expressed.
Therefore, qualitative data like intelligence, beauty and judgemental
information that cannot be expressed in numerical form, then
statistical methods cannot be employed on the same.
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Overview of statistical methods
According to John Dillard, in information age, to analyse a data and
conclude relevant result, it is essential to take right statistical tools.
It includes -
Mean: This method helps in determining the average value of large
information, to identify the overall trend of a data set. But
employing this method on data having skewed distribution, may
provide inaccurate information, that highly affects the decision
taken for achievement of business objectives.
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Correlation and Regression: Both methods are used to determine the
interdependence or relationship between two data, through which
trends over specific time can be analysed.
Standard deviations: It is mainly applied on data which is highly
spread for mean, that helps in determining the dispersion of data points,
in quick manner. But if data with strange patter like large amount of
outliers or non-normal curve, then desired information cannot be
obtained by applying standard deviation method.
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Types of data
Primary data: It includes quantitative business raw data i.e.
information without fabrication which can be collected from
primary sources only, such as questionnaire, survey and more.
Secondary data: It consists information which may undergone in a
statistical treatment and can be collected through government and
semi—government organisation, journals and other published
sources.
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Sources of data
Survey: This method is also called sample survey which is used to
estimate the characteristics of a large population data. Using this
method, gives advantage in to a company in determining the
current and previous trend more easily, but it can cause error also.
Samsung can use this source to collect feedback of customers and
other stakeholders about quality of products and services, so that
further improvement can be made.
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Census: It is based on each and every item of population to analyse data. Advantage of
using this method is getting accurate and more relevant information. But it includes
high cost and time, for analysing and interpreting the information.
Government and Semi-government sources: These sources provide data about current
and past performance of business of an organisation, through which a purpose behind
collecting the data can easily achieve. To collect data about competitive position of
own business and other competitors that deal in same market, managers of Samsung
can use this non-statistical source.
Continue
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Difference between a sample and a population
A population includes entire elements from a specific set of data, on which methods
like mean, median and mode, to conclude desired result. But if a population consists
large amount of data, then it is hard to apply these methods, because chance of error is
high under such case. While sample includes small size of data, that taken out from a
large population and includes every element which requires to obtain result. Applying
statistical methods on sample, gives advantage to calculate more accurate result, with
minor or negligible errors.
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Value of statistical methods
To achieve high competitive advantages in electronic business, where
competition is high, it is essential for Samsung to collect information
regarding with last five-year performance of competitors, their revenue and
more. By applying statistical methods like correlation, analysis of variance
(ANNOVA), hypothesis testing and more, managers of respective firm can
take effective strategies in improving and enhancing business performance.
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Difference between Descriptive and Inferential
Statistics
Basis of comparison Descriptive statistics Inferential statistics
Meaning This part of statistics
is mostly concerned
with explaining the
entire population,
from which specific
information can be
obtained.
It concerns with drawing the
conclusion on the basis of sample
observation.
Usage in business It helps in describing
the current, past as
well as forecasting the
situation of a
business.
It explains the chance of getting
success or meeting failure of
business in an organisation
Forms of result This method
represents
information in
graphical form like
charts, tables and
graphs
It provides probability of a result
How it works It elaborates the
complete data which
To determine the trend, it mainly
attempts to reach at conclusion.
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Key findings
Microsoft: SUMMARY
OUTPUT
Regression Statistics
Multiple R 0.9728245071
R Square 0.9463875217
Adjusted R Square 0.9454631686
Standard Error 6.0702620615
Observations 60
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Apple: SUMMARY
OUTPUT
Regression Statistics
Multiple R 0.9675382273
R Square 0.9361302212
Adjusted R Square 0.9350290181
Standard Error 9.8209074442
Observations 60
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References
Chatfield, C., 2018. Statistics for technology: a course in applied
statistics. Routledge.
Finkler, S. A., Smith, D. L. and Calabrese, T. D., 2018. Financial
management for public, health, and not-for-profit organizations.
CQ Press.
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