PRACTICAL RESEARCH 2

Quantitative Research

Is an objective, systematic empirical investigation of observable phenomena through the use of computational techniques. It highlights the numerical analysis of data hoping that the numbers yield unbiased results that can be generalized to some larger population and explain a particular observation.

Objective

Quantitative research seeks accurate measurement and analysis of target concepts. It is not based on mere intuition and guesses.

Clearly Defined Research Questions

The researchers know in advance what they are looking for. The research questions are well-defined for which objective answers are sought.

Structured Research Instruments

Data are normally gathered using structured research tools such as questionnaires to collect measurable characteristics of the population like age, socio-economic status, number of children, among others.

Numerical Data

Figures, tables, or graphs showcase summarized data collection to show trends, relationships, or differences among variables. In sum, the charts and tables allow you to see the evidence collected.

Large Sample Sizes

To arrive at a more reliable data analysis, a normal population distribution curve is preferred. This requires a large sample size, depending on how the characteristics of the population vary.

Replication

Quantitative methods can be repeated to verify findings in another setting, thus strengthen and reinforce the validity of findings eliminating the possibility of spurious conclusions.

Future Outcomes

By using complex mathematical calculations and with the aid of computers, if-then scenarios may be formulated thus predicting future results. Quantitative research emphasizes proof, rather than discovery.

Descriptive Research

This design is concerned with describing the nature, characteristics, and components of the population or phenomenon. There is no manipulation of variables or search for cause and effect related to the phenomenon.

Correlational Research

It is the systematic investigation of the nature of relationships or associations between and among variables without necessarily investigating causal reasons underlying them. It is also concerned with the extent of relationships that exists between or among variables.

Evaluation Research

This kind of research aims to assess the effects, impacts, or outcomes of practices, policies, or programs.

Survey Research

Is used to gather information from groups of people by selecting and studying samples chosen from a population. It may be done in various ways like face-to-face, phone, mail, and online.

Causal-Comparative Research

It is also known as ex post facto (after the fact) research. This kind of research derives conclusions from observations and manifestations that already occurred in the past and now compared to some dependent variables. It discusses why and how a phenomenon occurs.

Experimental Research

This research utilizes a specific method to test cause-and-effect relationships under conditions controlled by the researcher.

Quasi-Experimental Research

At least one variable is manipulated to determine the effect of the manipulation. Intact, naturally formed groups are used.

Variables

It is something that can take on different values for different subjects in a given research study.

Qualitative Variable

Data values are non-numeric and whose observations vary in kind but not in degree.

Quantitative Variable

Data values are numerical measurements and whose observations vary in magnitude.

Discrete Variables

Quantitative variables whose observations can assume only a countable number of values.

Continuous Variables

Quantitative variables whose observations can assume any one of the countless numbers of values in a line interval.

Nominal

Variables whose data values are non-numeric group labels that do not reflect quantitative information.

Ordinal

Variables where there is a meaningful order of categories but there is no measurable distance between the categories.

Interval

Variables whose data values are ranged in a real interval and can be as large as from negative infinity to positive infinity. It can also be when the difference between the two values is meaningful but the ratio of two-interval data is not meaningful. The interval date should also have arbitrary zero points.

Ratio

The highest level of measurement that has all the characteristics of the interval plus a true zero point. Both the difference and the ratio of two variables are meaningful.