Statistics for Management: Introduction, Techniques, and Applications

This presentation provides an introduction to statistics for management, including its characteristics and overview of techniques. It explains the difference between inferential and descriptive statistics and provides examples of sample datasets. The value of applying statistical techniques in meeting business objectives is also discussed. The presentation is relevant for the subject of Statistics for Management.

Statistics for Management

TABLE OF CONTENTS
INTRODUCTION
PART 1
Introduction of statistics with its characteristics and overview of techniques
Types and sources of the data that a business could access
Contrast between population & sample
Value of applying the statistical techniques in meeting the business objectives
Explaining difference between inferential and the descriptive statistics
Providing example of the sample dataset
PART 2
Evaluating difference between an inferential and descriptive statistics
Calculating range of the descriptive statistics
Presenting the findings
CONCLUSION
REFERENCES

INTRODUCTION
• Statistics for management provides an insights to the managers along with the
necessary tools in making sense of the larger quantities of the data.
• It focuses on making effective decisions in the business on the basis of the
inferences drawn from the dataset.

PART 1
Introduction of statistics with its characteristics and overview of techniques
Statistics is the collection of the methods or tools for the purpose of
planning, obtaining data, experiments and thereafter organising, presenting,
analysing, summarizing, drawing conclusion and interpreting the results on the
basis of data.

CONTD..
The main characteristics of statistics are as follows-
aggregate of facts
Affected by several causes
Expressed Numerically
Enumerated and estimated
Systematic manner

CONTD..
Overview of the methods-
There are mainly two main methods in statistics that could be used for assessing the data such as:

Types and sources of the data that a business could access
Researcher can gather or collect data using 2 method namely:

Contrast between population & sample
Population Sample
It means collection of each and every component
that possesses the common characteristics which in
turn comprises a universe.
It refers to the subgroup of population that is been
selected within the study.
The measurable quantity under population is called
as parameter.
However, under sample, a measurable quantity
referred as statistics.
The population is stated as the complete set. On the other side, Sample is counted as the part or
subset of population.
Under population, reports are been seen as the true
presentation of the opinions.
In sample, reports contains a margin of the errors
and a confidence interval.

Value of applying the statistical techniques in meeting the business objectives
Statistical method helps in setting up of the standards
Fixing quality norms for manufacturing the product, norms for daily output etc
helps in effective project planning, inventory planning, budgetary control, quality
control and personnel administration
used for ensuring quality of the production, determining or rejecting the defective
and substandard the goods
Assists in making decisions relating to facing of uncertainty

Explaining difference between inferential and the descriptive statistics
Inferential statistics Descriptive statistics
It means a kind of the statistics that emphasize
on inferring conclusion for sample assessment
and in generating observation regarding the
population.
It refers to the branch of the statistics that is
mainly concerned with describing a population
within the study. s
Inferential statistics test, predicts and compares
the data in effective manner.
Descriptive statistics organizes, present and
analyse the data in presentable and meaningful
way.
In inferential method, the final result is been
displayed in form of the probability.
There is a diagrammatic and tabular
representation of the final results in the
descriptive statistics.
It explains likelihood of occurring an event in a
particular situation.
It describes the entire situation and indicates all
the events present in an overall situation.

Providing example of the sample dataset
• Interpretation- From the graph it has
been stated that the COGS in terms of
revenue of Netflix is increasing in the
year 2016 from 2015 resulting as from
68% to 71%. However, thereafter in
the next years it started declining.

CONTD.. • Interpretation- From the above
chart or graph it has been indicated
that Net profit of Amazon is
increasing with a greater percentage
over the years. This shows that the
firm is performing in a better as it is
gaining increased profits by keeping
control over its expenses.

CONCLUSION
By summing up the above report it has been assessed that statistics
act as a crucial element fro the organization in order to make accurate
estimates regarding the future needs and goals and the ways in which
it could be attained effectively.
Moreover, hypotheses shows that significant difference is present
between mean value in the share price of the organizations and Index.

REFERENCES
Ho, A. D. and Yu, C. C., 2015. Descriptive statistics for modern test score distributions: Skewness,
kurtosis, discreteness, and ceiling effects. Educational and Psychological Measurement. 75(3).
pp.365-388.
Lindstromberg, S., 2016. Inferential statistics in Language Teaching Research: A review and ways
forward. Language Teaching Research. 20(6). pp.741-768.
McCarthy, R.V. and et.al., 2019. What Do Descriptive Statistics Tell Us. In Applying Predictive
Analytics (pp. 57-87). Springer, Cham
Mohammadi, M., Hofman, W. and Tan, Y. H., 2018. A comparative study of ontology matching
systems via inferential statistics. IEEE Transactions on Knowledge and Data Engineering. 31(4).
pp.615-628.
Sarstedt, M. and Mooi, E., 2019. Descriptive Statistics. In A Concise Guide to Market Research (pp.
91-150). Springer, Berlin, Heidelberg.
Trafimow, D. and MacDonald, J. A., 2017. Performing inferential statistics prior to data
collection. Educational and psychological measurement. 77(2). pp.204-219.

CONTD..
Trafimow, D., 2017. Using the coefficient of confidence to make the philosophical switch from a
posteriori to a priori inferential statistics. Educational and psychological measurement. 77(5).
pp.831-854.
Young, J. and Wessnitzer, J., 2016. Descriptive statistics, graphs, and visualisation. In Modern
statistical methods for HCI (pp. 37-56). Springer, Cham..
Online
Difference between population and sample. 2018. [Online]. Available
through:<https://keydifferences.com/difference-between-population-and-sample.html>