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Unit 6
Quantitative Data Analysis

Content
? 6.1 Types of quantitative data
? 6.2 Data coding
? 6.3 Visual aids for quantitative data analysis
? 6.4 Using statistics for quantitative data
analysis
? 6.5 Interpretation of data analysis results
? 6.6 Evaluating quantitative data analysis

Quantitative Data
? Quantitative data is the value of data in the
form of counts or numbers where each data
set has a unique numerical value.
? This data is any quantifiable information that
researchers can use for mathematical
calculations and statistical analysis to make
real-life decisions based on these
mathematical derivations.

Types of quantitative data
? Counter: Count equated with entities. For
example, the number of people downloading
a particular application from the App Store.
? Measurement of physical objects: Calculating
measurement of any physical thing. For
example, the HR executive carefully measures
the size of each cubicle assigned to the newly
joined employees.

? Sensory calculation: Mechanism to naturally
��sense�� the measured parameters to create a
constant source of information. For example, a
digital camera converts electromagnetic
information to a string of numerical data.
? Projection of data: Future data projection can be
made using algorithms and other mathematical
analysis tools. For example, a marketer will
predict an increase in sales after launching a new
product with a thorough analysis

? Quantification of qualitative entities: Identify
numbers to qualitative information. For
example, asking respondents of an online
survey to share the likelihood of
recommendation on a scale of 0-10.

Types of Quantitative data
? Nominal data : Nominal data is that which
describes categories and has no actual
numeric value. For example : Gender
? Ordinal data : With ordinal data, numbers are
allocated to a quantitative scale.
? A common use of ordinal data is in
categorizing responses to Like scale-based
questions, where numbers are assigned to the
range of responses.

? Interval data : Interval data is like ordinal data,
but now measurements are made against a
quantitative scale where the differences, or
intervals, between points of the scale are
consistently the same size, that is, the ranking
of the categories is proportionate.
? You can therefore state the difference
between any two data values precisely.

? Ratio data : Ratio data is like interval data, but
there is a true zero to the measurement scale
being used. For example, people��s age, weight,
or height, or companies�� number of
subsidiaries, head count of employees or
annual turnover.

Data Coding
? Data coding in research methodology is a
preliminary step to analyzing data.
? The data that is obtained from surveys,
experiments or secondary sources are in raw
form.
? This data needs to be refined and organized to
evaluate and draw conclusions.
? Data coding is not an easy job and the person or
persons involved in data coding must have
knowledge and experience of it.

What is a code?
? A code in research methodology is a short word
or phrase describing the meaning and context of
the whole sentence, phrase or paragraph.
? The code makes the process of data analysis
easier.
? Numerical quantities can be assigned to codes
and thus these quantities can be interpreted.
? Codes help quantify qualitative data and give
meaning to raw data.

What is data coding?
? Data coding is the process of driving codes from the observed
data.
? In qualitative research the data is either obtained from
observations, interviews or from questionnaires.
? The purpose of data coding is to bring out the essence and
meaning of the data that respondents have provided.
? The data coder extract preliminary codes from the observed
data, the preliminary codes are further filtered and refined to
obtain more accurate precise and concise codes.
? Later, in the evaluation of data the researcher assigns values,
percentages or other numerical quantities to these codes to
draw inferences.
? It should be kept in mind that the purpose of data coding is
not to just to eliminate excessive data but to summarize it
meaningfully.

Visual aids for quantitative data
Analysis.
? The simplest form of analysis uses tables and
charts to present the data in a visual way that
allows you to explore it and ��see�� values and
patterns in it.
? These tables and charts can also be included
in the write-up of your research, so the reader
sees what you see.

Tables
? Tables are suitable for use with all types of
data, and are easily produced using word
processing software.

Bar Charts
? Bar charts are often used for displaying
frequencies.
? The classic bar chart uses horizontal or vertical
bars (column charts) to show discrete, numerical
comparisons across categories.
? One axis of the chart shows the specific
categories being compared, and the other axis
represents a discrete value scale.
? They are best used to show change over time,
compare different categories, or compare parts of
a whole.

Pie Charts
? A pie chart is a graphical representation
technique that displays data in a circular-
shaped graph
? A pie chart is a pictorial representation of data
in the form of a circular chart.

Scatter graph
? A scatter graph can be used to show a relationship
between two variables.
? You plot your data as points on a graph, where the x-
axis represents the values of one variable, and the y-
axis represents the values of the other variable.
? If no line can be seen around which the data points
tend to cluster, then there is no relationship between
the variables.
? The more closely the points tend to cluster around a
line, the closer a relationship there is between the
variables.

Line Graph
? Line graphs are used for showing trends in
data,

References
? https://www.questionpro.com/blog/quantitat
ive-data/#Quantitative_Data_Definition
? https://readingcraze.com/index.php/data-
coding-research-methodology/

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RM UNIT 6.pptx

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