Quantitative or Qualitative
The discussion in this post will cover the effect of foundational belief system on the research method. The post will show the advantages and disadvantages of research sampling approaches, the data collection strategies and which data analysis procedures is more suitable for qualitative and quantitative data. The post ends by discussing how to conclude from the analyzed data and the differences in qualitative and quantitative conclusions.
Foundational belief systems
Human are influenced by social values and belief systems that shape their attitudes and behavior (O’Donohue & Nelson, 2009). Beliefs must be rationalized and justified to be believed. Values are at the heart of the belief system and difficult to change. Attitude is a hypothetical structure that represents individual’s like or dislike (Vaske & Donnelly, 1999). The influence of values on attitudes and behavior occurs indirectly via other components in the cognitive hierarchy. For example, basic beliefs serve to strengthen and give meaning to fundamental values. Patterns of these basic beliefs create value orientations.
Sampling the researched populations tremendously reduce the time needed to research the full population (Kitson et al., 1982). Research cost and effort are generously lowered when the researcher chose to sample the population (Kitson, et al., 1982). Kitson et al. (1982) state that sampling techniques are useful in generalizing the research results to a larger population because the sample fairly represent the larger populations. Researcher cannot determine the non-probability samples’ universe or its potential biases. The non-probability sample has huge advantage in developing hypotheses for future researches and low-frequency research issues (Kitson, et al., 1982). Data can be analyzed and interpreted easier when the population is small or when the sample is small and representative of the larger populations. The analysis easiness is found in the effort needed to analysis the data and the lower error probability.
Data Collection Strategies
The researcher is observer during the data collection and his or her role is mostly analyzing numerical numbers in the quantitative research. In the qualitative research, the researcher is involved in collecting, interviewing and analyzing the feedback received from the researched people. Data is typically reported textually in the qualitative research because the information is likely to be extracted from personal feedback during an interview or personal experience during survey filling. Interviews and meetings in the qualitative research needs extra effort spread over long period to cover most of the interviewees (Shank, 2006, p. 126). Qualitative research needs less effort and rather shorter period to collect the intended data.
Quantitative research include test and questionnaires that needs statistical calculation to understand. Quantitative research benefit from the existing databases for examination and cross-checking. Qualitative research take advantage of observations and focused groups (Dodd, 2008). One of the simplest and common research method is the case study which use interviews to study the person (Shank, 2006). Data collection in the quantitative research is done by using secondary data from the available databases.
Ethics and research integrity are important during the data collection. The research participant’s choice of involvement part of the ethical considerations in the research set up (Pyer, 2008). Crow, Wiles, Heath and Charles (2006) stress the importance of ethical practice during the research and data collection. Acting ethically during the data collection dose not conflict with the research effectiveness (Crow, Wiles, Heath, & Charles, 2006). Many researchers are concerned with the negative effect of ethical considerations on data collection quality, but Crow, Wiles, Heath and Charles (2006) discredit this concern. Crow, Wiles, Heath and Charles (2006) knowledgeable the need for informed consent even if the ethical and legal considerations are not part of the research.
Data Analysis Procedures
Quantitative analysis use statistical methods to analyze the research data to reach measurable relationship between the research variables. The quantitative analysis is perspective and mechanical in nature. The statistical methods are used to find visible trends in the research data (Creswell, 2005). The researcher sets the research questions, hypothesis and research design then collect the facts to begin analyzing it. The data cannot is analyzed after the collection completion. The experimental setup and survey data collection are relatively faster in the quantitative research than in the qualitative research.
Qualitative analysis is an investigative method to understand and interpret the data finding into meaningful results which can be generalized on larger group. Glaser (2009) value the grounded theory simplicity and the data analysis ease because of its low dependence on analytical skills. The qualitative data analysis needs smart questioning and persistent search for answers through active observation. In the qualitative analysis, the researcher engage in a back and forth dialogue with his data, according to Shank (2006). The researcher can analyze and interpret the data while the data collection is in progress.
Conclusions From Data
Researcher can achieve generalizations when different sample from the populations is tested and the same results were reached (Shank, 2006). Research results become questionable when the researcher could not duplicate the same results with different samples. Researchers bias in selecting the sample, due to personal preference or convenience, can skew the results. The disadvantages of sampling are the chance in not representing the population spectrum in the sample. Quantitative research analysis entail data manipulation to reach a meaningful results. The results are presented in numbers and mathematical models. The qualitative data analysis accomplish descriptive results which is explained in words (Creswell, 2005).
See also in this blog:
Creswell, J. W. (2005). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (2 ed.). Upper Saddle River, N.J.: Merrill Prentice-Hall.
Crow, G., Wiles, R., Heath, S., & Charles, V. (2006). Research Ethics and Data Quality: The Implications of Informed Consent. [Article]. International Journal of Social Research Methodology, 9(2), 83-95. doi: 10.1080/13645570600595231
Dodd, T. (2008). Quantitative and qualitative research data and their relevance to policy and practice. Nurse Researcher, 15(4), 7-14.
Glaser, B. G. (2009). The Novice GT Researcher. [Article]. Grounded Theory Review, 8(2), 1-21.
Kitson, G. C., Sussman, M. B., Williams, G. K., Zeehandelaar, R. B., Shickmanter, B. K., & Steinberger, J. L. (1982). Sampling Issues in Family Research. [Article]. Journal of Marriage & Family, 44(4), 965-981.
O’Donohue, W., & Nelson, L. (2009). The Role of Ethical Values in an Expanded Psychological Contract. [Article]. Journal of Business Ethics, 90(2), 251-263. doi: 10.1007/s10551-009-0040-1
Pyer, M. (2008). Unintended Consequences? Exploring the un(fore)seen effects and outcomes of research. [Article]. Children’s Geographies, 6(2), 213-217. doi: 10.1080/14733280801963227
Shank, G. D. (2006). Qualitative research: A personal skills approach (2nd ed.). Columbus: Pearson Prentice Hall.
Vaske, J. J., & Donnelly, M. P. (1999). A value-attitude-behavior model predicting wildland preservations voting intentions. [Article]. Society & Natural Resources, 12(6), 523.