1. Statistical analysis
"Department of Economics,
Entrepreneurship and Business
Administration"
https://econ.biem.sumdu.edu.ua/

2. 01
Definition of statistical analysis
The rise of big data, machine learning, and
technology in our society has created a
high demand for statistical analysts.
Therefore, statistical analysis as a branch of
science has become an integral part of life.
Statistical analysis is the process of
collecting and analyzing large volumes of
data in order to identify trends and develop
valuable insights.
In the professional world, statistical
analysts take raw data and find correlations
between variables to reveal patterns and
trends to relevant stakeholders.
This technique is
useful for collecting
the interpretations
of research,
developing statistical
models, and planning
surveys and studies.
Statistical analysis
involves working with
numbers and is used
by businesses and
other institutions to
make use of data to
derive meaningful
information.

3. 02
TYPES OF STATISTICAL
ANALYSIS
Descriptive Analysis
Inferential Analysis
Prescriptive
Analysis
Predictive
Analysis
Causal Analysis
helps describe, show or
summarize data points in a
constructive way such that
patterns might emerge that fulfill
every condition of the data.
is usually presented in the form of charts, graphs, and tables.
takes the results of descriptive statistics
one step further by drawing conclusions
from the data and then making
recommendations.
Inferential statistical analysis is often used by businesses to inform
company decisions.
is the process of using data to determine an optimal
course of action. By considering all relevant factors,
this type of analysis yields recommendations for next
steps.
is a type of statistical analysis that analyzes
data to derive past trends and predict future
events on the basis of them.
It uses machine learning algorithms, data
mining, data modelling, and artificial intelligence
to conduct the statistical analysis of data.
focuses on determining the cause and effect
relationship between different variables within
the raw data. In simple words, it determines why
something happens and its effect on other
variables.

4. 03
Importance of Statistical Analysis
Statistical analysis eliminates unnecessary information and catalogs important data in an
uncomplicated manner, making the monumental work of organizing inputs appear so orderly.
The statistical analysis aids in the effective design of laboratory, field, and survey
investigations.
Statistical approaches are used in the job of a businessman, a manufacturer, and a researcher.
Statistics departments can be found in banks, insurance businesses, and government agencies.
Statistical analysis can help in projecting the future financial needs of your company. This is
important in ensuring that you get enough time to plan for expansion. *Evaluating the productivity of your team
members and departments and identifying
measures you can take to boost productivity.
Politicians can utilize statistics to support and validate their claims while also explaining the
issues they address.
Statistical analysis may help with solid and efficient planning in any subject of study.
Statistics have long been of great importance to engineers, providing a powerful tool for
understanding the data collected from experiments and other activities.

5. Standard Deviation
1.
it analyzes the deviation of different data points from the mean of the entire data set.
Standard deviation is mainly used when you need to determine the dispersion of data
points (whether or not they’re clustered).
2. Hypothesis Testing
can be used to test the validity or trueness of a conclusion or argument against a data
set. It allows for comparing the data against various hypotheses and assumptions. It can
also assist in forecasting how decisions made could affect the business.
3. Mean
When this method is used it allows for determining the overall trend of a data set, as well as
the ability to obtain a fast and concise view of the data. Users of this method also benefit
from the simplistic and quick calculation.
4. Regression is a statistical tool that helps determine the cause and effect relationship between the variables.
It determines the relationship between a dependent and an independent variable.
5. Sample size determination
Sample size determination or data sampling is a technique used to derive a sample from the
entire population, which is representative. This method is used when the size of the
population is very large.
Statistical Analysis Methods
The 5 most used and popular methods of statistical analysis: