Statistics for Management Task 1: Data Analysis and Business Insights

This assignment solution for Statistics for Management Task 1 provides a comprehensive overview of statistical concepts and their applications in a business context. It begins by defining statistics and outlining its key features. The solution then explores different types of data, differentiating between primary and secondary sources, followed by a detailed contrast between population and sample, highlighting their respective roles in statistical analysis. The assignment further emphasizes the importance of employing statistical techniques to achieve business objectives, such as market research, ROI analysis, forecasting, and performance measurement. It also explains the differences between descriptive and inferential statistics, providing examples and illustrating their distinct approaches to data interpretation. The solution includes a relevant dataset example with graphical representation to demonstrate the practical application of statistical methods, analyzing financial performance indicators such as COGS and net profit ratios for companies like Netflix and Amazon. The conclusion summarizes the significance of statistics in business decision-making, with references to supporting literature.

STATISTICS FOR
MANAGEMENT

TASK 1
1. Meaning of statistics and its features
Statistics means an aggregate of the facts that is been affected to the
marked extent through various causes that is been expressed in
numerical terms, estimated and enumerated in accordance to the
reasonable accuracy standards.

Contd…
Characteristics of statistics
 Aggregate of the facts
 Numerically expressed
 pre-determined purpose
 systematic manner
 placed in place of each other
 Affected by various causes
 Estimated figures as per reasonable accuracy standards

Contd…
2. Types and the sources of the data information which a business required to
access
The business organization could access mainly two types of the data that includes
primary and the secondary sources of collecting data. Primary data reflects the
first-hand data that is been gathered in direct connection with the respondent
through personal investigation, questionnaire etc.
There are two main sources of the data that involves statistical and the non-
statistical sources.

Contd…
3. Stating contrast between population and the sample
Population Sample
Under this the measurable quality is referred in terms of the
parameter.
However, In sample, the quality measured is been stated as the
statistic.
It is been counted as the complete dataset for analysing and
drawing the conclusions on an overall population.
It is considered as the part or subset of population where as
small portion of the population is taken the data and it is been
assessed.
In this the reports are indicated as the true and accurate
representation of an opinion.
In sample, reports are having margin of the error and the
confidence interval.
It is comprised of all the members in a specified group. It means the subset which represents an entire population.
It involves complete enumeration of the items under the
statistical study.
It includes study of only the part of population and not entire
data.
Population is been seen as the specific interest group. Sample is choosing of the population from which the data is
been gathered.
Example- All the 5200 students had enrolled at the GHC during
2011.
For instance- 28 GHC are been surveyed out of total students
fro assessing a particular area of issue.

Contd…
4. Importance of employing the statistical techniques in achieving business
objectives
 Market research
 ROI
 Forecasting
 Performance measurement

Contd..
5. Explaining the difference between an inferential and descriptive
statistics
Descriptive statistics Inferential statistics
It is the methods that mainly concerns
with describing population within study.
It is the type of the statistics that mainly
focus on drawing the conclusions about
population as based on observation and
the sample analysis (Difference between
descriptive and inferential statistics,
2018).
It gathers, organizes, presents and assess
the data in meaningful manner.
On the other side, inferential statistics
makes comparison of the data, test the
hypotheses and makes predictions
relating to future outcomes.
In descriptive statistics, tabular
representation is been made of the final
results.
However, in this final outcome is been
presented in form of the probability.
It describes for a particular situation. On the other side, inferential statistics
depicts likelihood regarding occurrence of
an event.
This method explains the data that is
been already known in order to
summarize the sample.
Inferential statistics aims for reaching
conclusion for learning about population
which extends beyond availability of the

Contd…
6. Provide a relevant example of
the dataset with application or
employing of the statistical
methods with graph
6. Provide a relevant example of the
dataset with application or employing
of the statistical methods with graph
From chart given above it can be
observed that in year 2015 and 2016
COGS as part of sales revenue was 68%
and 71% but then it declines to 63%
which reflect that Netflix improve its
performance.

Contd… Net profit ratio of Amazon increased
from 1% to 4% which reflect that
firm control its direct and indirect
business expenses. It can be said that
firm successfully improve its
business performing by controlling
expenses in the business.

CONCLUSION
On basis of above discussion, it is concluded that there is significant importance
of the statistics because by using same firms easily measure their business
performance and make business decisions.

REFERENCES
 Parihar, S., 2018. Statistics for Management. South Asian Journal of
Management. 25(2). pp.226-229.
 Ribeiro, V. and et.al., 2017, August. Importance of Statistics for Data
Mining and Data Science. In 2017 5th International Conference on
Future Internet of Things and Cloud Workshops (FiCloudW)(pp. 156-
163). IEEE.
 Sotirchos, E. S., Fitzgerald, K. C. and Crainiceanu, C. M., 2019.
Reporting of R2 Statistics for Mixed-Effects Regression Models. JAMA
neurology. 76(4). pp.507-507.