This document provides an introduction to quantitative research methods. It defines quantitative research as a formal, systematic process of collecting and analyzing numerical data to find patterns, make predictions, test relationships, and generalize results. The key characteristics of research discussed are that it must be controlled, rigorous, systematic, valid and verifiable, and empirical. Common quantitative research methods include descriptive, correlational and experimental designs. Measurement, sampling, levels of measurement from nominal to ratio, and quantitative data analysis techniques such as descriptive and inferential statistics are also outlined. Finally, both the advantages of standardization and generalizability as well as limitations such as superficiality and structural bias are discussed.

1. Introduction to Quantitative
Research
Najibullah Safi, MD, MSc. HPM, MSc. PH

2. What is research?
• ‘A systematic and unbiased way of solving a problem (by
answering questions or supporting hypotheses) through
generating verifiable data.’
• Research is a process of collecting, analyzing, and
interpreting information to answer questions. But to qualify
as research, the process must have certain characteristics
• Qualitative research
• Quantitively research
• Mixed methods
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3. Characteristics of research
• Controlled - many factors can affect an outcome. In
exploring causality in relation to two variables, study is set
up in a way that minimizes the effects of other factors
affecting the relationship
• Rigorous - scrupulous in ensuring that the procedures
followed to find answers to questions are relevant,
appropriate and justified
• Systematic - this implies that the procedure adopted to
undertake an investigation follow a certain logical sequence.
The different steps cannot be taken in a haphazard way.
Some procedures must follow others
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4. Characteristics of research
• Valid and verifiable – The conclusion is valid and verifiable
meaning findings are correct and can be verified by others
• Empirical - Conclusions drawn are based upon hard evidence
gathered from information collected from real-life
experiences or observations
• Critical - The process of investigation must be foolproof and
free from drawbacks. The process adopted and the
procedures used must be able to withstand critical scrutiny
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5. Research methodology or methods
All the methods used by a researcher during a research study are
termed as research methods
• They are essentially planned, and scientific
• They include theoretical procedures, experimental studies,
numerical schemes, statistical approaches, etc.
• Scientific research methods call for explanations based on
collected facts, measurements, and observations and not on
reasoning alone
• They accept only those explanations which can be verified by
experiments
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6. What is quantitative research?
• Quantitative research is a formal, objective, systematic
process of collecting and analyzing numerical data
• It can be used to find:
• Patterns and averages
• Make predictions
• Test causal relationships
• Generalize results to wider populations
• Quantitative research is widely used in the natural and
social sciences: biology, chemistry, psychology, economics,
sociology, marketing, health etc.
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7. Quantitative research methods
• Quantitative research can be used for descriptive,
correlational, and experimental research
• In descriptive research, we simply seek an overall summary of
study variables
• In correlational research, we investigate relationships between
study variables
• In experimental research, we systematically examine whether
there is a cause-and-effect relationship between variables
• Correlational and experimental research can both be used
to test hypotheses
• Quantitative research is at risk for certain research biases,
including information bias, omitted variable bias, sampling
bias, or selection bias
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8. Measurement in quantitative research
• Measurement of different concepts should be valid or match
as much as possible the real world
• What is a concept?
• A mental construct that represents phenomena in the real
world
• The challenge is to transform concepts into concrete terms
(preferably that can be measured)
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9. Pollock’s model
Concept
Conceptual definition
Operational definition
Variable (a state that
takes different attributes
or values)
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10. A variable should be
• Exhaustive: should include all possible answerable responses
(schooling: no schooling, elementary, middle, high school,
college)
• Mutually exclusive: no respondent should be able to have
two attributes simultaneously (e.g., male and female)
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11. How do we construct quantitative variables?
• In order to operationalize our variables, we must first define
them and then select a means to construct them. We do this
by connecting concepts to observations
• This requires choosing a level of measurement
• Levels of measurement
• Nominal: Consists of categories that are non-ordered (e.g., gender, race)
• Ordinal: When numbers are used to order a list of things
• Interval: Variables of this type are called scalar or index
variables in the sense they provide a scale or index that
allows us to measure between levels
• Ratio: Like interval level variables in that it can measure the
distance between two points, but can do so in absolute
terms
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12. Measurement hierarchy
Nominal
Ordinal
Interval
Ratio
Weakest
Strongest
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13. Sampling
Terms
• Population: All possible subjects
• Sample: A subset of subjects
• Elements: One subject
What do we sample?
• People (e.g., subjects), places (e.g.,
hospitals), time (e.g., season)
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14. Type of sampling
Probability sampling: Can be done only if we have a
sampling frame
• Simple random sampling (using a random table of numbers)
• Stratified random sampling (divide or stratify by gender)
• Systematic random sampling (take every 5th name)
• Cluster random sampling (select unit)
Non-probability sampling:
• Convenience (e.g., first person to walk through the door)
• Purposive (setting criteria for respondents)
• Quota (e.g., an equal number of men and women)
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15. Quantitative data analysis
• Descriptive statistics: will give a summary of data and
include measures of averages and variability
• Also, we can use graphs, scatter plots, and frequency tables to
visualize data and check for any trends or outliers
• Inferential statistics: can make predictions or
generalizations based on data
• We can test hypothesis or use sample data to estimate
the population parameter
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16. Advantage of quantitative research
• Quantitative research is often used to standardize data
collection and generalize findings
• Strengths of this approach include:
• Replication: Repeating the study is possible
• Direct comparison of result: The study can be reproduced in
other settings, times
• Large samples: Data from large samples can be processed and
analyzed using reliable and consistent procedures through
quantitative data analysis
• Hypothesis testing
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17. Disadvantage of quantitative research
• Despite the benefits of quantitative research, it is sometimes
inadequate in explaining complex research topics
• Its limitations include:
• Superficiality: Using precise and restrictive operational definitions
may inadequately represent complex concepts
• Narrow focus: Predetermined variables and measurement
procedures can mean that you ignore other relevant observations
• Structural bias: Missing data, imprecise measurements
or inappropriate sampling methods are biases that can lead to the
wrong conclusions
• Lack of context: Quantitative research often uses unnatural
settings like laboratories or fails to consider historical and cultural
contexts that may affect data collection and results
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18. References
• Bhandari, P. (2022, November 24). What Is Quantitative Research?
Definition, Uses & Methods. Scribbr. Retrieved January 15, 2023, from
https://www.scribbr.com/methodology/quantitative-research/
• Introduction to quantitative research methods, a guide for research
postgraduate students at the University of Hong Kong. Retrieved
January 18, 2023, from
https://hub.hku.hk/bitstream/10722/191018/1/Content.pdf
• Saleem S. (2020). Introduction to research methodology in sexual and
reproductive health
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19. Thanks
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