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Key Elements of a Research Proposal
Quantitative Design
What are the main types of quantitative approaches to research?
It is easier to understand the different types of quantitative research designs if you consider how the researcher designs for
control of the variables in the investigation.
If the researcher views quantitative design as a continuum, one end of the range represents a design where the variables are
not controlled at all and only observed. Connections amongst variable are only described. At the other end of the spectrum,
however, are designs which include a very close control of variables, and relationships amongst those variables are clearly
established. In the middle, with experiment design moving from one type to the other, is a range which blends those
two extremes together.
There are four main types of Quantitative research: Descriptive, Correlational, Causal-Comparative/Quasi-Experimental,
and Experimental Research.
Types of Quantitative Design
Descriptive research Correlational research Causal-comparative/quasi- Experimental research, often
seeks to describe the attempts to determine the experimental research called true experimentation,
current status of an extent of a relationship attempts to establish cause- uses the scientific method to
identified variable. These between two or more effect relationships among the establish the cause-effect
research projects are variables using statistical variables. These types of relationship among a group of
designed to provide data. In this type of design, design are very similar to true variables that make up a
systematic information relationships between and experiments, but with some study. The true experiment is
about a phenomenon. The among a number of facts key differences. An often thought of as a
researcher does not usually are sought and interpreted. independent variable is laboratory study, but this is not
begin with an hypothesis, This type of research will identified but not manipulated always the case; a laboratory
but is likely to develop one recognize trends and by the experimenter, and setting has nothing to do with
after collecting data. The patterns in data, but it does effects of the independent it. A true experiment is any
analysis and synthesis of not go so far in its analysis variable on the dependent study where an effort is made
the data provide the test of to prove causes for these variable are measured. The to identify and impose control
the hypothesis. Systematic observed patterns. Cause researcher does not randomly over all other variables except
collection of information and effect is not the basis assign groups and must use one. An independent variable
requires careful selection of of this type of observational ones that are naturally formed is manipulated to determine
the units studied and research. The data, or pre-existing groups. the effects on the dependent
careful measurement of relationships, and Identified control groups variables. Subjects
distributions of variables exposed to the treatment are randomly assigned to
each variable. are studied only. Variables variable are studied and experimental treatments rather
are not manipulated; they compared to groups who are than identified in naturally
Examples of Descriptive are only identified and are not. occurring groups
Research: studied as they occur in a
natural setting. When analyses and Examples of Experimental
• A description of conclusions are made, Research:
how second-grade *Sometimes correlational determining causes must be
students spend research is considered a done carefully, as other • The effect of a new
their time during type of descriptive variables, both known and treatment plan on
summer vacation research, and not as its unknown, could still affect the breast cancer
• A description of the own type of research, as no outcome. A causal- • The effect of positive
tobacco use habits variables are manipulated comparative designed study, reinforcement on
of teenagers in the study. described in a New York attitude toward school
• A description of Times article, "The Case for • The effect of teaching
how parents feel Examples of Correlational $320,00 Kindergarten with a cooperative
about the twelve- Research: Teachers," illustrates how group strategy or a
month school year causation must be thoroughly traditional lecture
• A description of the • The relationship assessed before firm approach on students’
attitudes of between relationships amongst achievement
scientists regarding intelligence and variables can be made. • The effect of a
global warming self-esteem Examples of Correlational systematic preparation
• A description of the • The relationship Research: and support system on
kinds of physical between diet and children who were
activities that anxiety scheduled for surgery
typically occur in • The relationship • The effect of on the amount of
nursing homes, between an preschool attendance psychological upset
and how frequently aptitude test and on social maturity at and cooperation
each occurs success in an the end of the first • A comparison of
• A description of the algebra course grade the effect of
extent to which • The relationship • The effect of taking personalized
elementary between ACT multivitamins on a instruction vs.
teachers use math scores and the students’ school traditional instruction
manipulatives freshman grades absenteeism on computational skill
• The relationships • The effect of gender
between the types on algebra
of activities used in achievement
math classrooms • The effect of part-time
and student employment on the
achievement achievement of high
• The covariance of school students
smoking and lung • The effect of magnet
disease school participation
on student attitude
• The effect of age on
lung capacity
What is the basic methodology for a quantitative research design?
The overall structure for a quantitative design is based in the scientific method. It uses deductive reasoning, where the
researcher forms an hypothesis, collects data in an investigation of the problem, and then uses the data from the investigation,
after analysis is made and conclusions are shared, to prove the hypotheses not false or false. The basic procedure of a
quantitative design is:
1. Make your observations about something that is unknown, unexplained, or new. Investigate current theory surrounding
your problem or issue.
2. Hypothesize an explanation for those observations.
3. Make a prediction of outcomes based on your hypotheses. Formulate a plan to test your prediction.
4. Collect and process your data. If your prediction was correct, go to step 5. If not, the hypothesis has been proven false.
Return to step 2 to form a new hypothesis based on your new knowledge.
5. Verify your findings. Make your final conclusions. Present your findings in an appropriate form for your audience.
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