Taruc, Trisha Mae T.
November 23, 2020
BBE4301 – BJC
APPLICATIONS OF STATISTICS ON RESEARCH
GUIDE TO QUANTITATIVE AND QUALITATIVE DATA ANALYSIS
METHODS
QUANTITATIVE DATA
Quantitative data is the type of data whose value is measured
in the form of
numbers
or counts, with a unique numerical value associated with each data set.
Also
known as
numerical data
, quantitative data further describes numeric variables.
This data type can also be defined as a group of quantifiable information that can
be
used for mathematical computations and statistical analysis
which informs real-
life decisions.
QUANTITATIVE DATA ANALYSIS & INTERPRETATION
DATA PREPARATION
The first stage of quantitative data analysis and interpretation is data preparation, where
raw data is converted into something meaningful and readable
. There are four
steps of data preparation:
Step 1: Data Validation
This is done so as to find out whether
the data collection was done without
any bias. The process includes:
Testing for fraud by checking
whether all the respondents
were truly interviewed or not.
Screening the respondents to
know whether they really met
the research criteria.
Checking whether the right
procedure was followed.
Checking whether the investigation is complete.
Researchers do this by picking a random sample from a large population.

Step 2: Data Editing
Large data sets may inevitably include errors, and that is why they need to be edited.
During this process, data is inspected for completeness and consistency.
For example, a respondent may leave a field blank, which is a case of incompleteness.
In another case, we may have a respondent who answered that he/she has no children
also claim in another part that his(er) first child is in high school — this data is
inconsistent.
Step 3: Coding and Data Entry
This is the process of quantifying qualitative data for easy analysis. It involves grouping
and assigning values to survey responses. E.g. Male - 1, Female - 2.
Step 4: Data Transformation
This is the process of changing data into new format. For example, reducing a
5 point
likert-type scale
into 3 categories.
Consider a 5 point likert-type scale with the options very good, good, neutral, bad and
very bad. This may be reduced into good, neutral and bad.

DESCRIPTIVE STATISTICAL METHOD
Researchers make use of descriptive statistics to summarise quantitative data. It is
often used when analysing a single variable, and as such is sometimes called univariate
analysis. Some common descriptive statistical methods include:
Mean: the average of a set of numbers.
Median: the middle number of a set of numbers.
Mode: most occuring number from a set of numbers.
Range: the difference between the highest and lowest numbers from a set of
numbers.
INFERENTIAL STATISTICAL METHOD
This method measures the relationship (similarities and differences) between multiple
variables to generate results and infer conclusions. Some examples of inferential
statistics include; correlation, regression, ANOVA, etc
.