Lesson 1-5 Flashcards
Emphasizes objective measurements and the
statistical, mathematical, or numerical
analysis of data collected through polls,
questionnaires, and surveys, or by
manipulating pre- existing statistical data
using computational techniques.
Quantitative Research
Characteristics of Quantitative Research
• The data is usually gathered using
structured research instruments.
• The results are based on larger sample
sizes that are representative of the
population.
• The research study can usually be
replicated or repeated, given its high
reliability.
• Researcher has a clearly defined
research question to which objective
answers are sought.
• All aspects of the study are carefully
designed before data is collected.
• Data are in the form of numbers and
statistics, often arranged in tables,
charts, figures, or other non-textual
forms.
• Project can be used to generalize
concepts more widely, predict future
results, or investigate causal
relationships.
• Researcher uses tools, such as
questionnaires or computer software, to
collect numerical data.
• It tests theories or hypothesis.
Strengths of Quantitative Research
• It allows the research to measure and
analyze the data to arrive at an
objective answer to the problem
posed or stated.
• The results are reliable since the
study uses a big sample of the
population.
• It is real and unbiased.
• The numerical data can be analyzed
in a quick and easy way.
• Quantitative studies are replicable.
• Process involved is simplified.
Weaknesses of Quantitative Research
• Quantitative research requires a
large number of respondents.
• It is costly.
• The context of the study or the
experiment is ignored in such a way
that it does not consider the natural
setting where the study is conducted.
• Results are limited.
• Much information are difficult to
gather using structured research
instruments.
• If not done seriously and correctly,
data from questionnaire may be
incomplete or inaccurate.
• It provides less elaborate accounts of
human perceptions.
• Preset or fixed alternative answers
may not necessarily reflect the true
answers of the participants.
• also referred as Survey Research that
can be used to get more details and tries
to find, to describe the existing status of
a variable or phenomenon.
Example:
Business and Market researchers that want to observe habits and traits of consumers or
brand users.
Drescriptive Design
explores the relationship between variables
using statistical evaluation and use to
receive more statistical data.
Example:
The amount of money a person has might
positively correlate with the number of most
number of assets and companies he has.
correlational design
➢ It is collected of research designs which
use manipulation and controlled testing
to understand causal process.
➢ One or more variables are manipulated
to determine the effect on a dependent
variable.
Experimental Design
➢ which is also known as Causal
Comparative method seeks to begin a
cause effect relationship between two or
more variables.
➢ Involves selecting groups, which a
variable is tested without any random
pre-selection process.
Quasi-Experimental Design
Importance of Research in Education
▪ Strategies
▪ Innovations, programs, and action plans
▪ Students’ attitude and behavior
▪ Curriculum and planning
Importance of Research in Science and technology
▪ Innovation & inventions
▪ Advancement
▪ Scientific knowledge
Importance of Research in Business
▪ Products and services
▪ Sales and management strategies
▪ Consumer’s satisfaction
Importance of Research in Medicine
▪ New medications
▪ Costumer and facilities satisfaction
▪ Performance
Importance of Research in Language and Linguistics
▪ Understanding of stylistic and linguistic
approach
▪ History of language
▪ Context of language
Importance of Research in Communication
▪ Communication phenomena
▪ Process of understanding a message
Importance of Research in Anthropology
▪ Human understanding of past and
present
▪ Culture and historical background of
people
Importance of Research in Social Sciences
▪ Societies and the relationship among
individuals
▪ Typically survey and experiment
• Any factor or property that a researcher
measures, controls or manipulates.
• Changing quantity or measure of any
factor, trait, or condition that can exist
in differing amount or types.
Variables
➢ Also known as manipulated or
explanatory variable.
➢ a variable that stands alone and isn’t
changed by the other variables you are
trying to measure.
Independent Variable
➢ Also known as response or predicted
variables.
➢ the result of the independent variable
being changed.
➢ something that depends on other factors.
➢ the variable being tested and monitored
and are those that are influenced by the
independent variables
Dependent Variable
➢ Also known as interval variable.
➢ are numeric variables that can take any
value, a variable that can be used for an
infinite number of possible values.
➢ Time, age, temperature, height, weight,
etc.
Continuous variable
➢ are numeric variables that come from a
limited set of numbers.
➢ may result from answering questions
such as “how many” “how often” and how far or that can only take on a certain number of values.
➢ These are variables use that are
countable where the range of specified values is complete
➢ Classroom attendance, number of
children in a family number of sections in a grade level, etc.
Discrete Variable
➢ Are variables with values that describe a
quality or characteristics of a data unit
like “what type” or which category”
➢ Ordinal variables and nominal variables
Categorical Variable
2 types of Categorical Variable
Nominal
-ex. hindi na oorganize in a logical sequence: religions, sports
Ordinal
-ex. na oorganize: with honors, with high ( ranks sa school )
➢ in research is any variable that can
potentially play a role in the outcome of
a study, but which is not part of the
study
- epekto ng extraneous
Confounding Variable
