Research Design
The research design is the overall strategy chosen to integrate different components coherently and logically, thus ensuring an effective address to the research problem. It constitutes blueprints for data collection, measurement, and analysis (Anastas, 2008). The research design is effectively determined by the type of research problem that the researcher is solving. The main function of the research design is to ensure that the evidence obtained effectively addresses the research problem more logically and unambiguously. The research design has been categorized into two types. The first is a quantitative design, including correlation, causal-comparative, experimental, and quasi-experimental. The second one is the qualitative design, which includes the case study and the historical, the narratives, the grounded theory, and the phenomenology. Different research designs can be combined to come up with effective results.
Sample Selection
Sample selection is choosing the subset of the individuals from the statistical population based on the estimated characteristics of the population. The advantages of sample selection include the low data collection cost and a fast measurement of the entire population. There are two types of samples. The first one is a probabilistic sample, which is the true representative of the population being researched, and a non-probabilistic sample, which does not truly represent the sample being researched. The probabilistic samples include random samples where each population is equally likely to be selected and stratified samples where the population is divided into characteristics before selection. On the other hand, non-probabilistic involves quota samples, purposive samples, and convenience samples. The nonprobabilistic samples are limited in generalizing the information since they don’t represent the true population.
Data Collection Methods
Research requires more accurate information relating to the problem being studied. The information and the data can come from a wide range of sources. Therefore, a variety of methods are needed to gather primary data. Some of the techniques needed in the data collection include interviews, which are structured for the quantitative research design. It includes face-to-face interviews, telephone interviews, and computer-based personal interviews. The second one is a questionnaire and survey (Hall, 2008). The paper and pencil questionnaire can be sent to a larger population group. The Internet questionnaire is very cheap and faster than the paper questionnaire. The third is observation, which allows the study of dynamic situations. The fourth is the focus groups, and the other methods include ethnographies, case studies, and the oral history. Documents and records are the other forms of secondary data collection.
Plans For Data Analysis
For any data analysis process, it requires the creation of a proper plan. The plan for the data analysis is an illustration of the basic requirements for the research. The plan illustrates the data structure, the declaration of the research objectives, and the description of the sources of the data and the information (Hanks, 2017). Then, it’s important to identify the procedures that are to be used in carrying out the research. This implies that the plan must also include the methods that will be used to collect and analyze the data. Therefore, the research document becomes vital in the research since it illustrates methods and the purposes of the research to the supervisors, experts, researchers, and the grand writers while in the field of research.
Bibliography
Anastas, J. W. (2008). Research Design for Social Work and the Human Services. New York: Columbia University Press.
Hall, J. (2008). Cross-Sectional Survey Design. Encyclopedia of Survey Research Methods, 173-174.
Hanks, G. (2017, September 26). How to Write a Data Analysis Project Plan. Retrieved from Bizfluent: https://bizfluent.com/how-6744253-write-data-analysis-project-plan.html
