Statistical Applications in Business: An In-depth Analysis

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Statistics Management

Introduction....................................................................................................................................3
Task 1..............................................................................................................................................4
P1.....................................................................................................................................................4
P2.....................................................................................................................................................5
P4.....................................................................................................................................................6
Task 2..............................................................................................................................................7
Conclusion....................................................................................................................................16
References.....................................................................................................................................17

Introduction
The given report helps to give out a clear image of the aspects or points relating to statistics that
normally arise in almost business situation. With the passage of time, it has come to the
observation that statistics is extensively used in the business decision making process.
Accordingly, it can be observed that there statistics is using continuously in almost every aspect
of business decision making since there are various fields in which statistics can be successfully
applied. It is important to understand the fact that statistics cannot be applied in qualitative field
of business.

Task 1
P1
Statistics is used to define the nature and extent of relationship that exist between any given two
or more than two variables. Such definition usually helps to take various crucial decisions at
various phases in every decision making of every business enterprise. There are certain factors
that need to be take care of while drawing reasonable and meaningful conclusion and meaningful
interpretation. It becomes essential to duly take into consideration all these factors during
analysis and interpretation.
It can be said that there are several benefits and advantages of statistics in meeting or
accomplishing business objectives. These objectives should be in line with the business
dynamics continuously taking place in the environment.
The following are the essential characteristics of the statistical data:
Useful in decision making process: This is the most integral characteristics of statistical data.
As such, it can be said that the output or result derived from the application of various statistical
tools and techniques can be used to take meaningful successful and important various decisions
(Chartier and Cousineau, 2011).
Cause and effect relationship: Statistics helps to identify cause and effect relationship between
the given variables. These variables can be two or more than two. Furthermore, these variables
can be quantitatively expressed pressed.
Numerically expressed: Generally, the variables taken for the purpose of the data analysis and
interpretation should be numerically expressed. In other words, it can be said that the taken
variables must contain numerical figures or values.
Specific or predetermined purpose: It is essential that the data collected for a specific purpose.
Without predetermined purpose, useful and meaningful interpretation can be made and that too
with ease. Only then collected data will have significance.

There are several aspects that normally arise in the application of statistics in the various field of
business. Although, it is almost impossible to discuss each and every aspect of statistics due to its
instinct characteristics, an attempt has been made to discuss some of the major points which
almost every business man faces in varied decision making process.

P2
There are different methods of analyzing the derived and collected data. Selection of method
depends on the various factors or characteristics. The first and foremost factor for the selection of
the method is the nature and characteristics of the collected data.
These methods have to be carefully selected for the betterment of outcome. For the accurate and
correct outcome, it is imperative to have a clear as well as an in depth knowledge of all the
implications of these several methods. An in depth and a complete understanding of all the
applicable methods make the selection much more easily thereby assisting the data analysis or
research team. There methods have different implications and thus application of these methods
requires different phases or steps (Kim, 2015).
For this purpose, it is advisable to have for the data or research analyst to consult with the team
members comprising the overall research team. Such discussion will help to identify and
determine the most optimum and most feasible method of data analysis and interpretation of
data.
Since, data analyzing is the most crucial and yet complex phase of data collection and analyzing,
choosing and selecting the most appropriate method or approach is of utmost importance. Only
then the purpose of data collection can be achieved (Koen and Holloway, 2014).
Statistics can play a vital role in achieving the purpose or goal of a business organization for
which it has been established or constituted. It can be said that without such application it is
almost impossible to accomplish the desired and required business goals and objectives.

P4
There are various statistical methods that can be applied to the usage and purpose for which it
has been prepared or drafted. Selection of the most appropriate and most optimum statistical
method depends heavily on the field of business in which it is going to applied. Necessary
precaution need to be carefully applied so as to derive the better outcome or result. It is expected
while choosing and selecting the statistical method, the data analyst is fully aware of the area in
which it is going to be applied. This will enhance or improve the productivity and thereby the
value of the applied statistical method (Mrkvicka, et. Al., 2016).
It may be possible that one particular method can be applied in a particular situation but cannot
be applied in another situation. This is because of the fact that there are various characteristics of
statistics and it is almost impossible to define the characteristics in a single term. This is because
of the fact that statistics is a dynamic and its distinct features keep on changing from time to
time. Apart from that, statistics is very flexible indicating that its scope and ambit keeps on
changing from time to time. In other words, it can be said that the application of statistics totally
depends on the data analytical team or the person responsible for analyzing the collected data.
Some theorists also argue and are of the view that such selection of analytical tool also somewhat
depends on the data collection team or the person responsible for the collection of the relevant
data (Lu and Zhang, 2010).

Task 2

In T-test analysis,
two-tail test is conducted such that if the value of that data comes between stat <-t critical 2 tail
or t-stat >t critical two tail, then in such case a null hypothesis is not acceptable. In the 4th
scenario, from the available of the given one condition is satisfied, therefore the test accepts the
null hypothesis. In the fourth condition, available data moreover same it means not change so
much.

In Annova testing,
a null hypothesis is worked or based on when F > F Crit, if this situations comes then it will be
rejected. In the above 4 cases, F Crit is less as compare with the value of Fin all the given cases.
It means the data not so much changes over the time and it create a condition that value of mean
may be same.

The data that represent from the Chi-square testing gives null results in the entire provided data.
It suggest that there is no link between the expected data and the observations from such array of
information (Sharpe, 2015).
Important aim of the descriptive statistics analysis is that available data make more easy and in
meaningful manner so that calculation can be easy because the main purpose is for the
calculation, thus it makes easier for the individual person to make conclusions from such
represented data whereas inferential analysis provides more decisive data for the process of
decision making (Ott, 2018).

Statistical function is divided into two categories, descriptive and inferential analysis. Both are
the used for the purpose of analyzing the performance in numerous functions. Hence the need
and requirement may change as depend on situation so it may vary according to the situation.
Descriptive analysis does not include so much calculations and it work on raw data, while
inferential analysis draws conclusions depend on based data.