Quantitative Research Methodology

Introduction

Creswell (2003) defines quantitative research as a systematic methodology used to measure how a particular number of people feel, think or behave in a certain manner. The methodology uses samples to obtain quantitative data through interviews, questionnaires, or observation. It is the systematic analysis of quantitative properties and aspects as well as the relationship between them. It is a widely used concept in all aspects of the study and its objective is to develop mathematical models or theories that relate to particular natural phenomena.

Quantitative research in a proposed study normally answers the questions of what, where, and when. It is an interactive way of evaluating evidence from theories and models. Some examples of quantitative research in our day to day way of living includes (Porte 2003):

1. Research that incorporates the percentage amounts of all the atmosphere’s elements.
2. An analysis that summarizes the average number of patients who have to wait a certain time before being treated.
3. An experiment in which a certain group of patients was given drug X in respect to another group of patients that were given drug Y, in which case each member in the two groups is randomly selected.

This shows that quantitative analysis can be used to relate two or more aspects in terms of measurement to come up with a definite solution for the study.

Quantitative Research – A Description

According to Creswell (2003), quantitative research in a study tries to answer the questions why, what, when, and where about the subject matter. This helps to show the validity and strengths of the ideas as well as the credibility of data to be used by the audience or users of the research.

Quantitative Research – Describing What

Quantitative research normally attempts to describe the major steps that the researcher intends to use during the study. This provides a guideline of areas that are to be covered and the concepts that will enable the researcher to effectively carry out the study. It acts as a charter that helps the researcher to define the concepts directed towards his study. The researcher addresses the statement of the problem and aims at focusing the study on the statement (Creswell 2003).

Quantitative Research – Describing When

Once quantitative research methodology has described the concept of what, it then looks at the period in which the research will be carried out. The period also determines the duration that the research is likely to take. The scope of the research is defined and the study is based on this scope. Tools like time series are used to determine the time during which the research was carried out. The researcher should take reasonable time so as to ensure that the set time is neither too little for extensive research to be done, nor is it too much that a lot of resources in respect to time and cost are used up. In respect to time, the researcher must ensure that they are consistent because any withdrawal of resources in between the research periods may result in different research outcomes (Scott 1988).

Quantitative Research – Describing Where

According to Scott (1988), quantitative research also answers the question of where the intended location for the study is to be. It gives information about where the research is to be carried out. Data collection procedures and the cost of carrying out the research normally differ with any change in location. Changing the location of the study may also affect the validity of the data and may result in different outcomes at the end of the research.

Quantitative research and its strengths as a research design

Quantitative research helps to determine the relationship between two variables, the dependent variable and the independent variable in a particular study area. There are two types of quantitative research designs, namely (Scott 1988):

1. Descriptive research designs, where the variables are determined only once. These designs establish the relationship between the two variables.
2. Experimental research designs where data is made before and after an experiment or treatment. Experimental research design establishes the cause of an event.

Scott (1988) argues that in order to accurately estimate the relationship between two variables, descriptive research requires that a sample of many observations is taken and experimental research requires that only a small number of observations are taken. On the other hand, in order to get an unbiased estimate of the relationship of variables, the sample must be selected randomly from a particular population. The observations should also be taken from a study group that is highly participative.

It is important to know that in all studies, the characteristics of the different observations may affect the relationship of the variables being researched upon. To limit the effects of these characteristics, one may decide to use a more identical set of observations or may quantify the characteristics and then include them in the analysis (Murray, 2003).

Quality of quantitative research designs

According to Berger (2000), the various quantitative designs vary in the quality of evidence that they provide towards the cause and effect relationship of the dependent and independent variables. A properly designed case-control study can provide sufficient evidence for the lack of any relationship among variables. However, if the study shows a relationship, then the researcher may be portraying only suggestive evidence of a cause-and-effect relationship. A case-control study is therefore an effective way of deciding what designs to implement.

A Prospective study is another way of showing quality in quantitative designs. The prospective studies are more difficult to perform but they give sufficient evidence and provide a reliable conclusion for the variables’ cause and effect relationship. There are also experimental studies that provide the best evidence on the relationship of variables. They explain and prove the way in which one variable affects another (Berger 2000).

Descriptive studies try to portray a confounding issue on the cause-and-effect relationships. This occurs when the relationship between two variables arises when there is a casual relationship with a third variable. This means that the results obtained are greatly influenced by a third variable other than the two main cause and effect variables (Berger 2000).

Strength of quantitative research design

Scott (1988) argues that the methodology of quantitative research has its research design strengths. For quantitative research to be meaningful, it must contain empirical data that is valid and which has been measured with statistical analysis being made to obtain the most sufficient inferences. Quantified data portrays images and pictures that bring about credibility and quality to its users. It also gives researchers a clear stand to make predictions, come up with conclusions and cite further questions for further studies.

According to Scott (1988), quantitative research design also enables researchers to identify the appropriate relationships between variables, establish their cause and effect, and give information on why a certain action is necessary or why a particular behavior is being demonstrated. Quantitative data shows greater strength than qualitative data in terms of giving value to subjects, which is easily understood by every user.

Quantitative Research Design – Some Precautions

One major characteristic of quantitative research designs is that after the structure has been put in place it is not easy to make changes to it. For instance, if a model measures seven factors and in course of the research, the researcher finds out a new factor it may be difficult to add that additional factor without interfering with the research and the factor may be very important in obtaining the relevant findings. The researcher may however incorporate a test before measuring the actual model in order to be able to identify any changes that may likely arise (Scott 1988).

According to McNabb (2002), a pilot group can also be used to make observations of the subject matter and avoid any future change in the research design structure. A pilot study is performed to help develop, adapt, or confirm the appropriateness of techniques. They are important in determining the reliability of the quantitative measures as well as in calculating the required size of the final samples. The pilot study should have the same sampling procedure as in the larger study in order to identify its appropriate sample.

Strengths and Weaknesses of Quantitative Research

Quantitative Research methodology has its strengths and weaknesses and these must be taken into consideration while implementing it. The advantages of quantitative research methodology include (Creswell 2003):

1. Metric measurements are easier to understand than theoretical measurements. This means that one can easily relate the values to the actual concepts that are being researched. They are also easy to explain unlike when using qualitative data.
2. In quantitative research, it becomes easy to assign measurable values to a particular observation and this makes the analysis less complex and easier to be compared with data from other researches.
3. A metric measurement gives us a statistical quantity in terms of knowing the values of the different observations and this enables researchers to be able to summarize data of a big population with much ease.
4. Quantitative data can also be visually represented in tables, charts, and graphs in order to help convey the effects of the results obtained. For instance, from the pie charts created out of the quantified data, one can relate the different subjects with the results and obtain relevant conclusive evidence of performance.
5. The metric measurements also easily allow managers to define their long-term strategies towards enhancing the results obtained. This is because large samples can be researched upon and the findings obtained quantified to come up with projectable data that can be used for future planning.

On the other hand, quantitative research has its own limitations which make qualitative data more sufficient than quantitative data. Creswell (2003) has come up with the following limitations:

1. In this methodology, large samples are needed in order to justify the population study. Gathering a sufficient and large sample may create difficulties and may lead to sabotage of the study. The large samples may not be easy to incorporate into the study.
2. It is also an expensive methodology because collecting a large sample of data means that more costs are incurred. The researcher would be required to spend more of his/her resources in coming up with a substantial analysis of the data obtained from the large sample.
3. Since quantitative research requires that researchers carry out short and time-saving interviews, inaccuracies may be experienced in the data obtained and if it is not properly handled, then the findings will result in statistical errors.
4. Quantitative research methodology is also rigidly structured as it attempts to cover a large sample area and this lack of flexibility may also result in a statistical error.
5. Large samples are meant to justify the entire population, but with the large amount of data taken, it may be difficult to make a generalization on the population especially when the observations are subject to human behavior.
6. The misuse of sampling procedures and the assigning of metric measurements may vary with the different researchers and this may greatly affect the accuracy and validity of the quantitative research methods. In this aspect, bias fr5om the researcher affects the final findings of the quantitative research methods.
7. On the other hand, the correlation of a large number of variables can expand the data of the observation and this may, in turn, affect the desired scope of the study. Changing the scope of the study would mean that the design also be changed and it may cause more complexities while analyzing data.

Qualitative and quantitative research

According to McNabb (2002), qualitative research is used to analyze and understand different people’s experiences, attitudes, and interactions in a particular aspect. It formulates non-metric data through description rather than through numerical value of something. In health care, qualitative research methods have been used to record experiences of chronic illnesses and to analyze the functions of the various health organizations.

In quantitative research techniques, in-depth interviews are used to find out more about a particular study. The views of the interviewees are therefore very important in this kind of methodology (McNabb 2002).

Quantitative research on the other hand works with data that can be converted into numbers and it is from the analysis of these numerical values that conclusive evidence of the research is obtained.

Introducing a Qualitative Factor in a Quantitative Study

Punch (2005) argues that the logic of relating qualitative and quantitative methodology is an issue of across-method triangulation and quantitative methods are almost by definition an issue of “across-method triangulation”. The meaning of triangulation may be obtained from the concepts of social sciences as being a means towards combining results from different methods of analysis. It can be given three meanings, namely:

1. Triangulation is the mutual combination of results obtained by using different methods, that is, the validity model.
2. Triangulation may also be a means towards deriving a larger and more complete picture of the subject being studied. In this case, it is referred to as the complementarity model.
3. Triangulation process shows that combining different methods is important as it helps to gain a clearer picture of the relevant concepts. This definition of triangulation may be referred to as the trigonometric model.

These three meanings of triangulation as used in social sciences are then brought up to give the potential outcomes of the relationship between combining qualitative and quantitative techniques together in a particular study. In order to determine the successful applicability of the triangulation models in introducing a qualitative factor in the quantitative analysis, the considerations need to be related to the actual research process (Punch 2005).

Creswell (2003) argues that the three mixed methodologies are used to bring out the effectiveness of incorporating qualitative aspects into the quantitative aspect of the study. The triangulation method of combining different studies is not only the methodological consideration but also the theoretical aspect of it. It can be argued that it is the triangulation model which sufficiently enables the effectiveness of combining the qualitative and quantitative methods.

The need for the combination of both methodologies is, despite its benefits, a long way from the actual research work and it does not give enough ideas on how this kind of combination may be achieved. The integration of qualitative research into the quantitative research methodology stands to gain such that none of the methodologies are ignored or left out in any research. In the case of the quantitative analysis, there will be greater proximity towards the research subject when the qualitative methodology is incorporated. The qualitative methodology on the other hand will benefit by making the different stages of research to become more systematic and transparent and therefore improve the generalization of findings (Punch 2005).

According to Creswell (2003), the mixed methodology is taken as one effective way of providing the best kind of research while taking into consideration the complexities associated with the studies of inherent human behavior. By mixing a qualitative factor with the quantitative aspects, the research users are able to have a substantial perspective of the numerical data that has been collected.

Social science research has in the recent past advocated for the use of mixed methodologies in both quantitative and qualitative research in bringing out the desired results of a particular study. This will help in the evaluation of the phenomenon and providing a sufficient basis for obtaining a particular result.

Concepts that relate both to quantitative and qualitative research

Porte (2003) has come up with the following concepts that have been used by both quantitative researchers and qualitative researchers to help them understand the methodologies. These are:

Association: In most studies, there is a relationship between the variables but these variables may not be dependent upon one another. This means that there may not be a causal relationship between the variables.

Bias: Both quantitative and qualitative research is subject to bias from the researcher. This means that the findings obtained in both are sometimes subjective.

Causal relationship: This is a relationship in which one behavior results in another or behavior brings about a particular consequence. Quantitative and qualitative research shows the causal relationships of two or more variables.

Hawthorn effect: This is a psychological response from the subjects of observation once they discover that they are being studied. The Hawthorn effect on subjects may alter the findings of the research in both quantitative and qualitative data.

Pilot studies: This is a small trial that is carried out before the actual research work in order to ensure that either the qualitative or quantitative research design is effective for the particular study.

Population: This means the entire group from which a sample is taken for the research process. It refers to all members of the group from which information is obtained.

Reliability of data: This is concerned with the accuracy of information obtained, either in the qualitative aspect of the quantitative form. It is the measure of data representing the true score of the observations in the research. In reliability of data, the same results must be obtained in any study at different times and regardless of who is carrying out the research. Reliability reduces the chances of bias while obtaining results and ensures accurate conclusions are made.

Representativeness: This refers to the extent to which a sample shows the actual aspects of the entire population. Samples should be made in a way that they represent the entire population. The results obtained from the sample should be used as a representative of the entire population because it is not possible to observe all the subjects in the population.

Validity:

This refers to whether a particular research instrument both in qualitative methodology and quantitative methodology actually measures the construct that it is designed to analyze. Different tools are validly used to measure specific constructs.

Sampling: This means selecting a small number of subjects from a large population so that the subjects selected may be representative of the population being studied. The way that a sample is selected must be clearly illustrated in the research so that the user of the research may understand the findings and relate them to the population. The sample selected must be unbiased and must be representative of the entire population. In this aspect, it is important that the appropriate way of sample selection is made.

Conclusion

Quantitative research methodology has been used for a long time to obtain data in research and it has been referred to the qualitative research. However, with time it has become clear that the two methodologies could be incorporated together and still come up with valid results. Quantitative research design has been considered one of the most sufficient ways of obtaining data because it was easily understood and was less subjected to personal bias. It has continuously been used in all aspects of life like in hospitals, schools, public sectors, and other research institutions.

In respect to the social sciences, it has been noted that quantitative research may not work on its own. This is because some information relevant in research may not be quantified in numerical values and with this; qualitative research was put into use. It has become an efficient way of analyzing and interpreting information or results using non-metric forms. It has also been observed that with the mixed methodologies, quantitative research has been improved and it can now be used to analyze the social aspect of data.

It can be concluded that there are three main elements of a researcher’s results. These are:

1. A substantial contribution towards the existing methodology of research or knowledge.
2. Ability to show proof of appropriate application of the different research methodologies before undertaking any research work.
3. Ability to gather sufficient evidence to support all the findings obtained and any conclusions made.

It is important also to know that even if quantitative research has a number of advantages over qualitative research, mixing the two methodologies has proved to be an effective way of enhancing the quantitative research methodology.

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