SW-Popular statistical data analysis tools and techniques used in market research.pdf

powerful open-source programming language and environment used for statistical computing and graphics. It offers a wide variety of statistical techniques, including linear and nonlinear modeling, time-series analysis, classification, and clustering. R is widely used in academia, research, and industry for data analysis.

1. POPULAR STATISTICAL
DATA ANALYSIS TOOLS
AND TECHNIQUES USED
IN MARKET RESEARCH
An Academic presentation by
Dr. Nancy Agnes, Head, Technical Operations, Statswork
Group  www.statswork.com
Email: [email protected]

2. Outline
TODAY'S DISCUSSION
In-Brief
Introduction
Data analysis techniques
Data Analysis Tools
Conclusion

3. In-Brief
Statistical data analysis is a method used for performing numerous statistical It is a
survey-based analysis technique that helps market research to determine how people
value various attributes (feature, function, benefits) which makes up an individual
product or service.

4. Statistics is fundamentally a science that includes data
interpretation, data collection, and data validation.
Statistical data analysis is a process of accomplishing
various statistical operations.
It is a kind of quantitative research, which seeks to quantify
the data, and applies some form of statistical analysis
Quantitative data involves descriptive data, such as survey
data and observational data.
Introduction
Contd...

5. Market Research And Competitive Statistical Analysis: Market research is how
product managers gather information about customer needs and market drivers.
Competitive Statistical is the subset of market research. Numerous data analysis
tools and techniques are existing in the market, having its own set of functions.
The choice of tools should always be based on the type of analysis conducted, and
the data used.

6. REGRESSION ANALYSIS:
The statistical techniques used to carry out the
relationship between two or more variables.
A variation in the dependent variables mainly depends
on and is associated with, a change in one or more
independent variables.
Linear regression- It uses an independent variable to
predict the result of the dependent variable.
Multiple regressions –It uses at least two independent
variables.
Data Analysis
Techniques
Contd...

7. For example: Analyzing a particular organization or retail shop, before and after
advertising.
The money the store spends on publicity will be considered as an independent
variable; the number of people will be the dependent variable.
Online Statistical Analyses Services Help gives you a clear guidance about
conducting an effective survey.
Contd...

8. The resulting graph obtained from the regression analysis shows the regression
curve.
It shows the impact of money on publicity, whether it increases or decreases: only
in some rare cases data will be directly proportional, so some degree of the curve
will always be on the graph.
Contd...

9. ANALYSIS OF VARIANCE (ANOVA) TEST:
It is used along with regression to identify the effect of independent variables
over the dependent variable.
It compares multiple groups simultaneously to find the relationship between them,
e.g. analyzing whether a different type of advertisements gets different consumer
responses.
CONJOINT ANALYSIS:
It is a survey-based analysis technique that helps market research to determine
how people value various attributes (feature, function, benefits) which makes up
an individual product or service.
Contd...

10. The ultimate aim of conjoit analysis is to identify at what combination the
attributes is effective for the respondent choice
A controlled set of possible products or services is displayed to the survey
respondent.
By analyzing how they decide on choosing the products, the implicit evaluation of
the individual elements makes up the product or service can be determined.
These implicit valuations generate market models that evaluate market share,
income and even success of new designs.
Contd...

11. Market researchers always love to predict people.
To identify some fundamental reasons, why people make complex choices.
And conjoint analysis is close to this; it inquires people to create trade-offs while
creating decisions, just as they carry out in the physical world, then examines the
outcomes to give the most popular result.
If you find difficulty with the survey-based analysis, you reach Professional Help
With Analysis Of Statistical Data to get efficient research work.
Contd...

13. THE T-TEST
A T-Test help to associate two data groups which have different mean values,
e.g. do male and female have different mean heights? The t-test enables the user
to interpret whether differences are meaningful or merely coincidental.
It is used to identify the significant difference between the mean of two clusters,
which may be connected in certain aspects.
It is one of many tests used for hypothesis testing in statistics.
Professional Help with Analysis of Statistical Data helps you to get an effective
test.
Contd...

14. Contd...
Calculating a T-Test requires three fundamental data values,
The mean difference that is a difference between the mean values from
each data set
The standard deviation of each group, and
The number of data values.
DESCRIPTIVE ANALYSIS:
It takes the historical data, Key performance indicators, and elaborates the
performance based on the selected benchmark.
It considers the past trends and how they might impact future
performance.

15. DISPERSION ANALYSIS:
It is an area onto which a data set is spread. This technique helps the data
analysts to identify the variability factor which is under study.

FACTOR ANALYSIS:
This method used to determine the existence of a relationship between
groups of variables.
This process reveals factors or variables which describe the patterns in the
relationship among the original variables.
Contd...

16. Numerous data analysis tools are existing in the
market, having its own set of functions.
The choice of tools should always be based on the
type of analysis conducted, and the data used.
The following are the list of few Data Analysis tools
used for compelling.
TABLEAU:
It comes under the BI Tool category, created for
individual data analysis purpose.
Data Analysis
Tools
Contd...

17. The soul of Tableau is the Pivot Table and Pivot Chart and works towards
demonstrating data in the most user-friendly way.
It also contains a data cleaning feature along with brilliant analytical functions.
POWER BI:
It started as a plugin for Excel, and later it detached from it to create one of the
most powerful data analytical tools.
It has three different versions.
Contd...

18. It consists of a power pivot and DAX language, which help implement
sophisticated advanced analytics similar to writing Excel formulas.
Online Statistical Analyses Services Help you with handling various data
analysis tools.
R & PYTHON:
R & Python are the powerful and flexible programming language; R is used for
statistical analysis, such as cluster classification algorithms, normal
distribution, and regression analysis.
Contd...

19. It also helps in an individual predictive analysis like customer behaviour, their
expenditure, and their preferred items based on their browsing history, and so on.
It also includes machine learning and artificial intelligence concepts.
SAS:
SAS is a data analytics and data manipulation programming language, which can
effortlessly access data from various resources.
SAS has presented a broad set of customer profiling products for web, social
media, and marketing analytics.
It can predict their behaviours, manage, and optimize communications.
Contd...

20. Conclusion
Statistical consulting for dissertations is our exclusive
focus.
And which is essential for many fields and offers
extensive potentials to people in need of it.
Statistical Analysis And Consulting Services are
popular and applied in every aspect of society because
it ensures adequate and successful functioning of an
organization.

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