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Quantitative research
an objective, systematic empirical investigation of observable phenomena through the use of computational techniques. It highlights numerical analysis of data hoping that numbers yield unbiased results that can be generalized to some larger population and explain a particular observation.
Phenomenon
any events that are observable, however common it might be, even if it requires the use of instrumentation to observe, record, or compile data concerning it.
Quantitative Research
“explaining phenomena by collecting numerical data that are analyzed using mathematicallybased methods (in particular, statistics)." (Aliaga and Gunderson, 2000)
Quantitative research
collecting numerical data to explain a particular phenomenon. It is more logical and data-led approach which provides a measure of what people think from a statistical or numerical point of view. The data gathered are not based on intuition or gut feelings but rather on actual observation based on measurable facts.
Quantitative research
can gather a large amount of data that can be easily organized, analyzed and interpreted.
Objective
Clearly Defined Research Questions
Relationships or differences between variables
Presence of theories and hypotheses
Structured Research Instruments
Numerical Data
Concise Visual Presentation
Large Sample Size
Generalized Data
Faster Data Analysis
Fast and Easy Data Collection
Replicability
Future Outcomes
Characteristics of Quantitative Research
Objective
Data gathering and analysis of results are done accurately, objectively, and are unaffected by the researcher’s intuition and personal guesses.
Clearly Defined Research Questions
Research questions are well-defined for which objective answers are sought.
Relationships or differences between variables
Quantitative research investigates how a certain cause (IV) affects the result (DV). Other variables are controlled in order to assure that the effect is only due to the applied variable under a study.
Presence of theories and hypotheses
Quantitative research answers only theories and hypothesis related to the problem on hand. It does not make an assumption of the truth but rather tries to prove the truth from being offered.
Structured Research Instruments
Data are normally gathered using structured research tools such as questionnaires to measure characteristics of the population
Numerical Data
Data are in the form of numbers and statistics.
Concise Visual Presentation
Data is numerical which makes presentation through graphs, charts, and tables possible and with better conveyance and interpretation.
Large Sample Size
To obtain more meaningful statistical result, the data must come from a large sample size.
Generalized Data
Data taken from a sample can be applied to the population if sampling is done accordingly, i.e., sufficient size and random samples were taken.
Faster Data Analysis
The use of a statistical tools gives way for a less timeconsuming data analysis.
Fast and Easy Data Collection
Depending on the type of data needed, collection can be quick and easy. Quantitative research uses standardized research instruments that allow the researcher to collect data from a large sample size efficiently.
Replicability
The quantitative method can be repeated to verify findings enhancing its validity, free from false or immature conclusions.
Future Outcomes
By using complex mathematical calculations and with the aid of computers, if-then scenarios may be formulated thus predicting future results.
It is objective.
The use of statistical techniques facilitates sophisticated analyses and allows to comprehend a huge amount of vital characteristics of data.
The numerical data can be analyzed in a quick and easy way.
Quantitative studies are replicable.
Data analysis is relatively less time consuming (using statistical software) and the results are relatively independent of the researcher (statistical).
Strengths of Quantitative Research
Quantitative research requires a large number of respondents.
It is costly.
The information contextual factors to help interpret the results or to explain variations are usually ignored.
Many information is difficult to gather using structured research instruments, specifically on sensitive issues like pre-marital sex, domestic violence among others.
If not done seriously and correctly, data from questionnaires may be incomplete and inaccurate.
Errors in selection of procedures for determining statistical significance can result in erroneous findings regarding impact.
Research methods are inflexible because the instruments cannot be modified once the study begins.
Weaknesses of Quantitative Research
Descriptive Research
Correlational Research
Evaluation Research
Survey Research
Causal-Comparative Research
Experimental Research
Kinds of Quantitative Research
Descriptive Research
describes the nature, characteristics, and components of the population or a phenomenon. There is no manipulation of variables or search for cause and effect related to the phenomenon.
Correlational Research
systematic investigation of the nature of relationships, or associations between and among variables without necessarily investigating into causal reasons underlying them. It is also concerned with the extent of relationships that exists between or among the variables.
Positive Correlation
Negative Correlation
No Correlation
Types of Correlation
Positive Correlation
an increase of one variable will lead to an increase in the other, and a decrease in one leads to a decrease in another.
Negative Correlation
an increase in one variable will lead to the decrease of another
No correlation
two variables are uncorrelated when a change in one doesn’t lead to a change in the other and vice versa.
Evaluation Research
aims to assess the effects, impacts or outcomes of practices, polices, or programs.
Survey Research
gathers information from groups of people by selecting and studying samples chosen from a population.
Cross-sectional
Longitudinal
Types of Survey Research
Cross-sectional
the information is collected from a sample in just a single point of time.
For example: child-rearing practices of single parents, population control practices of unmarried couples
Longitudinal
collects information on the same subject over a period of time, sometimes lasting many years in order to study the changes through the years.
For example: determine the growth of rice field in the country, the rate of promotion of doctorate degree holders five years after earning the degree
Causal-Comparative Research
It is also known as ex post facto (after the fact) research. This kind of research derives conclusion from observations and manifestations that already occurred in the past and now compared to some dependent variables. There is an alleged cause-and-effect that has already occurred and is being examined after the fact.
Experimental Research
utilizes scientific method to test cause-and-effect relationships under the conditions controlled by the researcher. The basic purpose of this type of research is to investigate the influence of one or more variables.
Experimental Research
This is an experiment where the researchers manipulate one variable, and control or randomize the rest of the variables.
Variable
is the central concept in research and a measurable characteristic that changes in value. The value can vary from one person, place, thing, or idea depending on the issue at hand.
Based on Scales of Measurements
Based on Value taken by the Variable
Based on Cause-and-Effect
Kinds of Variable
Qualitative Variables
Quantitative Variables
Based on Scales of Measurements
Qualitative Variables
are those that are not expressed in numerical forms.
Nominal Variables
Ordinal Variables
Qualitative Variables
Nominal Variables
have two or more categories, in no particular order. (e.g. sex, eye color, religion, civil status)
Ordinal Variables
have two or more categories just like nominal variables except that the categories can be ordered or ranked. (e.g. satisfaction of services: Not Very Much, Much, Very Much; academic award: With Honor, With High Honor, With Highest Honor)
Quantitative Variables
presented in terms of numbers, a measurable quantity. It can take an infinite number of values and may not be measured accurately and can take on any value between its minimum and maximum value. (e.g. age, height, temperature)
Interval variable
Ratio variable
Quantitative Variables
Interval variable
a measurement where the difference between two values does have a meaning. The interval between values makes sense and can be interpreted.
Ratio variable
possesses the properties of interval variable and has a clear definition of zero, indication that there is none of that variable.
Continuous Variables
Discrete Variables
Based on Value taken by the Variable
Continuous Variables
can take on any value in a certain range. These are measurements with fractional values. (e.g. time, distance, mass, age, temperature, pH)
Discrete Variables
assume exact values and has no fractional unit. (e.g. number of siblings, population of students)
Independent variable
Dependent variable
Based on Cause-and-Effect
Independent variable
the cause variable or the one responsible for the conditions that act on something else to bring about the changes
Dependent variable
the outcome variable or the result or effect of the changes brought about by another variable(independent variable)
3-5 pages
How many pages should the Background of the Study have?
Scope, Context, and Importance
The 3 main elements that should be included in the Background of the Study
Scope
The research problem you’ll be covering. Start with a general overview of your problem. From general to specific, macro to micro approach. You may include concepts and ideas related to the problem including clarification or important terminologies.
Context
The background of your topic
Context
Review other conclusions and results on your topic. Include both older scholars and modern scholars. This background information shows that you are aware of prior research. It also introduces past findings to those who might not have that expertise.
Importance
Why your research matters in the context of an industry or the world
Importance
The rationale for one's research is the justification for undertaking a given study. It states the reason(s) why a researcher chooses to focus on the topic in question, including what the significance is and what gaps the research intends to fill. In short, it is an explanation that rationalizes the need for the study.
Statement of the Problem
This part of briefly describe the condition or a situation that exists which is perceived as something less than ideal.
First Part: Objective or Purpose of the Study
It is a statement of a long-term objective to be achieved by the study. It is derived by the identification and formation of the research problem and as reflected in the title. It answers the 5W’s (What, Who, Where, Why, When).
Second Part: Research Questions
These are the specific questions which are to be answered in the study. The answers to the research questions should lead to the solution of the research problem. It should be observable, measurable, and verifiable.
Quantitative Research Questions
Are designed to investigate the significance and relationship between variables and often involve the manipulation of an independent variable to observe its effects on a dependent variable.
Hypothesis
Are statements in quantitative research in which the investigator makes a prediction or a conjecture about the outcome of a relationship among attributes or characteristics.
Simple
Specific
Testable
Characteristics of a Good Hypothesis
Simple
A hypothesis should be direct to the point. The language must not have double meaning. It is necessary that the hypothesis should only show relationship between one independent variable and one dependent variable, or show differences of two or more groups.
Specific
A specific hypothesis leaves no ambiguity about the subjects and variables, or about how the test of statistical significance will be applied. It is formulated from specific questions which they are based.
Testable
A testable hypothesis could be proven right or wrong depending upon the outcome of the experiment.
Null Hypothesis
This states that there is no relationship between independent and dependent variables or no difference between groups of an independent variable or a dependent variable.
Null Hypothesis
This is the assumption you are beginning with and the opposite of what you are testing.
Alternative Hypothesis
This is the opposite of the Null Hypothesis. This will state the nature of the connection between or among the variables that the researcher expects.
Alternative Hypothesis
It shows that there is a significant difference/relationship between the variables that were being tested.
Directional/One-Tailed alternative hypothesis
Nondirectional/Two-Tailed alternative hypothesis
2 Types of Alternative Hypothesis
Directional or One-Tailed alternative hypothesis
The researcher predicts the direction of a change, a difference, or a relationship for variables in the total population of people.
Nondirectional or Two-Tailed alternative hypothesis
The researcher predicts a change, a difference, or a relationship for variables in a population but does not indicate whether the direction of this prediction will be positive or negative, or greater or less.
Scope
It describes the coverage of the study. It specifies what is covered in terms of concept, number of subjects or the population included in the study, as well as the timeline when the study was conducted.
Why, What, Where, When, Who, and How
6 W’s that Scope of the Study Aims to Identify
Why
The general aims and objectives (purpose) of the research.
What
The subject to be investigated, and the included variables.
Where
The location or setting of the study, i.e. where the data will be gathered and to which entity the data will belong.
When
The timeframe within which the data is to be collected.
Who
The subject matter of the study and the population from which they will be selected. This population needs to be large enough to be able to make generalizations.
How
How the research is to be conducted, including a description of the research design (e.g. whether it is experimental research, qualitative research or a case study), methodology, research tools and analysis techniques.
Delimitations/Limitations
Refer to the boundaries of the research study, based on the researcher’s decision of what to include and what to exclude. They narrow your study to make it more manageable and relevant to what you are trying to prove.1. Research variables, 2. target populations, and 3. statistical analysis techniques
Limitations
Are characteristics of the research design or methodology that are out of your control but influence your research findings. Because of this, they determine the internal and external validity of your study and are considered potential weaknesses.
Issues with sample and selection
Insufficient sample size, population traits or specific participants for statistical significance
Lack of previous research studies on the topic which has allowed for further analysis
Limitations in the technology/instruments used to collect your data
Limited financial resources and/or funding constraints.
Examples of Limitations
Significance of the Study
The researcher defines who will benefit out of the findings of the study. This section describes how the problem will be solved and specifically pinpoints who will benefit from such findings or results.
Significance of the Study
Usually, the beneficiaries of the study are those experts concerned about the problem. The beneficiaries are arranged from most benefited to least benefited.
Definition of Terms
This section is a list of key terms or important terms that will be discussed in the study. This is arranged alphabetically and to be presented in complete sentences.
Conceptual Definition
Operational Definition
2 Types of Definitions in the Definition of Terms
Conceptual definition
Defining terms based on actual concepts based on what has been accepted as the definition used by the experts in the area.
Operational definition
Terms should be clearly defined according to how they are used in the study for an easy understanding of the problem and avoid ambiguous meaning to terms that can be otherwise interpreted in different ways.
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