Statistics for Management: Overview, Application, and Examples

This presentation provides an overview of statistics for management, including the importance and application of statistical techniques in achieving competitiveness and objectives. It explains the contrast between descriptive and inferential statistics and provides examples of datasets. The presentation also covers the evaluation of descriptive and inferential data, as well as the application of different statistical methods. The subject is Statistics for Management, and the document type is a presentation.

STATISTICS FOR MANAGEMENT

TABLE OF CONTENTS
INTRODUCTION
Part 1
Overview of statistics
Sources and the kind of the information accessed by the business
Difference between the sample and population
Explaining the value of application of the statistical techniques in respect of achieving competitiveness and objectives
Explaining contrast between inferential & descriptive statistics with implication in respect of the business intelligence
Providing appropriate examples of given dataset
PART-2
Evaluating contrast between an inferential and descriptive data
Application of the range of different statistical methods
Presenting the finding in an appropriate format
CONCLUSION
REFERENCES

INTRODUCTION
 Statistics management provides the managers with tools that are important in making
sense of the large quantities of the data and making the most suitable business decisions
on the basis of the inferences drawn from the data.
 Collecting a numerical history of the occurrence factors on the optional repairs or the
processes which helps in determining requirement for the accurate quantities of the
material for smoothing delay at the time of production fluctuations.
 The present report is based on statistical management within which various statistical
measures are been highlighted that helps the firm in evaluating its performance.

Part 1: Overview of statistics
 Statistics is the form of the mathematical analysis
 It is counted as the aggregate of the facts that are been expressed in the numerical form.
 statistic is stated as the discipline which is concerned with collection, displaying,
interpreting, organizing and presenting the data.
 Helps in analysing trend and thereby gives input for taking corrective measures for
improvement

Sources and the kind of the information accessed by the business
Mainly there are two main methods
through which the data can be collected by
the business under statistical management
Specifically, there present two main
sources of the data that includes statistical
and non-statistical sources. Statistical
sources means the data that is been
gathered for official purposes:

Difference between the sample and population
Basis Population Sample
Meaning It refers to collecting all the elements that
possess common attributes which comprises
universe.
It means the sub-group of members of the
population that is been chosen for involving
more and more participation in study.
Inclusion Population includes each and every single
unit of group (Difference between population
and sample, 2018).
It involves only handful population units
under the study.
Features The main characteristics of population
involves the parameter.
Statistic is one of the most important
characteristic of sample.
Data collection In a situation when the information is
gathered from all the units of the population
then the process is called as complete
enumeration or census.
However, sample survey is been conducted in
gathering the information from sample by
making use of the sampling techniques.
Emphasize on Along with the population, the main focus is
to determine characteristics of components.
On the other side, in sample, the main
emphasize is on making generalisation
regarding the attributes of population from
which sample had been developed.

Explaining the value of application of the statistical techniques in
respect of achieving competitiveness and objectives
 Helps the managers in analysing previous performances, forecasting the future business
practices and leading the organization effectively.
 helps in dealing with the information and in making use of it in more effective way in
the context of decision making.
 Assessing effectiveness and efficiency of the functioning within individual departments
and also in improving their performance on the continuous basis.
 Give inputs for future planning

Explaining contrast between inferential & descriptive statistics
with implication in respect of the business intelligence
Basis Descriptive statistics Inferential statistics
Meaning It means that the branch of the statistics that
is concerned with describing a population
under the study.
It is the type of statistical technique that
emphasize on reaching to conclusions
relating to the population based on the
sample analysis and an observation.
Purpose The main purpose of applying the descriptive
tool of statistics is organizing, analysing the
present data in more meaningful way.
Under this the data is been compared,
predicted and tested in an effective manner.
Final result form The result generated under this is been
reflected in from of charts, tables and graph
(Contrast between inferential and descriptive
statistics, 2019. ).
Under inferential statistics, the result are been
shown in form of the probability.
Use Descriptive technique is mainly been used for
describing a particular situation.
In order to explain possibility of occurrence
of a specific event.
function It describes the data that is already been
known in summarizing the sample.
This technique attempts for reaching to
conclusions for learning about population
which extends beyond the available data.

Providing appropriate examples of given dataset
Qbic Hotel
Years Revenue Profits
2014 150000 50000
2015 200000 70000
2016 220000 110000
2017 250000 130000
2018 270000 160000
Mean 218000 104000

PART-2: Evaluating contrast between an inferential and descriptive
data
Descriptive data- It means numbers that are been used for summarizing and describing the
data. under this the data is been used for providing description about population either
through the numerical computations or by the tables and the graphs.
Advantages Disadvantages
 It is stated as the sensitive measure as it reflects values of all
data in final calculations.
 Descriptive statistics is the not been affected by the extreme
results.
 This tool is most useful at the time when data is expressed in
categories.
 It is counted as the precise measure of the dispersion where
all exact values are been taken into consideration.
 Through this technique calculation of variance is not been
seen as difficult.
 It makes easy computation of the range within the dataset.
 This method cannot be used in the situation where the data
is nominal.
 This method requires the interpolation for the group
aggregate data in form of cumulative frequency curve.
 It might not be characterize when the items in data are few
and is distributed irregularly.
 Under this very limited use of the statistics has been made
and cannot determine exact value in the group data.
 It opts for very limited use of the statistics which results in
inaccurate findings.

Contd..
Inferential data- Under this inferences and the predictions regarding population is based
on sample of the data that is been taken from population.
Advantages Disadvantages
 Large predictions are been made from the small
sets of data under inferential statistics.
 It provides for inferring conclusions from the
adequate sample in relation to the population.
 Under this data are been used from the small
group fro making generalisations about the larger
group of the people within the population.
 This method provides an estimate of the unknown
parameters that could be used fro making
predictions on the distributions which are been
known in a better way.
 Inferential statistics majorly applied on the basis
of utilizing the values that is measured in sample
fro anticipating or inferring the values that would
measure in the population. In order to be more
and more concrete, problem is the degree of the
uncertainty present while providing the data
about the population.
 It needs for making estimations on part of the
user on the theory to run it so again there present
some sort of uncertainty within this process that
will be having any repercussions on certainty of
results under the study.

Application of the range of different statistical methods
Descriptive statistics: Netflix
Total
Revenue
Cost of
Revenue
Gross
Profit
Researc
h
Develop
ment
Selling
General
and
Administ
rative
Total
Operatin
g
Expenses
Operatin
g Profit
or Loss
Interest
Expense
Profit
Tax
Expense
Net
Profit
Mean 10774 7212 3562 902 1878 9992 782 235 45 520
Standard
Error 1953 1156 817 123 397 1661 299 66 16 250
Median 10262 7145 3116 867 1640 9652 609 194 46 373
Mode #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A
Standard
Deviation 3906 2313 1633 247 794 3322 597 132 33 499
Range 9015 5376 3639 571 1768 7715 1299 288 59 1089
Minimu
m 6780 4591 2188 651 1231 6474 306 133 15 123
Maximu
m 15794 9968 5827 1222 3000 14189 1605 420 74 1211

Netflix Netfli
x
Parti
cular
s
2018 2017 2016 2015
Total
Reve
nue
15,79
4
11,69
3
8,831 6,780
Gros
s
Profit
5,827 3,660 2,573 2,188
Oper
ating
profit
1,605
839 380 306
Net
profit 1,211
559 187 123

Ama
zon
Partic
ulars
2018 2017 2016 2015
Total
Reve
nue
2328
87
1778
66
1359
87
107006
Gros
s
Profit
9373
1
6593
2
4772
2
35355
Oper
ating
profit
1242
1
4106 4186 2233
Net
profit
1007
3
3033 2371 596

Amazon

Presenting the finding in an appropriate format

Contd..
Regression analysis: Netflix
Regression Statistics
Multiple R 0.959235
R Square 0.920133
Adjusted R Square 0.918756
Standard Error 30.35722
Observations 60
df SS MS F
Signific
ance F
Regressi
on 1
615791.
1
615791.
1
668.204
6 1.6E-33
Residua
l 58
53450.5
3
921.560
8
Total 59
669241.
7

CONCLUSION
 By summing up the above report, it has been summarized that application of
statistical tools helps in drawing appropriate results and helps the firm in taking
adequate decisions and also in achieving the objectives effectively and efficiently.
 Furthermore, hypotheses has been created for Netflix & Amazon in respect of its
dataset in accordance with index fro understanding the relationship among the variables
and assessing the significance difference between the mean value of the share prices of
an organization.

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Krickeberg, K., Van Trong, P. and Hanh, P. T. M., 2019. Descriptive Data Analysis and
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Contd..
Monsen, K. A., 2018. Descriptive Analysis and Interpretation. In Intervention Effectiveness
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Nuijten, M. B., 2019. Practical tools and strategies for researchers to increase
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Contd..
Online
Contrast between inferential and descriptive statistics. 2019. [Online]. Available
through:<https://keydifferences.com/difference-between-descriptive-and-inferential-
statistics.html>
Difference between population and sample. 2018. [Online]. Available
through:<https://keydifferences.com/difference-between-population-and-sample.html>