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 assessed before firm • A description of the • The relationship approach on students’ relationships amongst attitudes of between achievement variables can be made. scientists regarding intelligence and • The effect of a global warming self-esteem systematic preparation • A description of the • The relationship Examples of Correlational and support system on kinds of physical between diet and Research: 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.