Introduction
Quantitative research design involves the acquisition of a sample through random or purposive sampling techniques and then the sample is used for statistical analysis. The findings of the statistical analysis are then used to make an inference about the population. Quantitative data focuses on the use of numerical data and statistical tests which require certain requirements to be met. Quantitative research methods just like the other methods assist the researchers to obtain important information using limited resources and time restrictions.
In most cases, experimental methods involve the use of control and experimental groups where the control group undergoes a treatment to regulate for a particular effect. The experimental group, however, does not undergo any treatment and this will enable the comparison of the control and experimental group so as to establish if the treatment was significantly effective or not. Experimental methods rely on random sampling and it in most cases involve the manipulation of the independent variable so as to observe the effect on this causes on the independent variable. Apart from the treatment, there are no differences between the control and the experimental groups so that any difference in the post test data can be considered to be as a result of the treatment. Internal validity in experimental methods can be attributed to extraneous variables if these variables can entirely be ruled out as the cause of a specific experimental outcomes. External validity is the ability of an outcome to be generalized outside that specific experiment. Some threats to internal validity in experiments include experimental changes in the course of the experiment and outcome, changes in measures as a reaction to the measurement process and participants changes in the course of the experiment (Groove, 2007).
Survey method on the other hand employs probability sampling and as such the more the number the better as this will enable the data to conform to the central limit theorem. In addition, this allows the sample to be a representative of the population which the inference will be made. It involves systematic questions which are not 'leading' as this would create bias. Similar to experimental methods it involves numerical data and probabilistic conclusions. The limitations of survey method is ethical considerations as it limits the acquisition of participant information from other sources. The complication in determining casual relationships between variables is also a point of concern. Reliability is the ability of the items of a questionnaire to measure the variable of interest consistently. It is important in research as it allows the researcher to quantify the variable being measured and as such it prevents the deviation of the research objective. Validity is the ability of a outcomes of a research to symbolize the phenomenon that was being observed in the study. It is the ability of sample statistics to be representative of the population parameters. Validity is important as it justifies the application of the statistical analysis results to make an inference on the population (Boslaugh, 2008).
References:
Boslaugh, S., & Watters, P. A. (2008). Research design. In Statistics in a nutshell. Sebastopol, CA: O'Reilly Media, Inc. Retrieved from http://proquest.safaribooksonline.com/book/-/9781449361129
Grove, Susan K. (2007). Statistics for Health Care Research: A Practical Workbook. Edinburgh: Elsevier Saunders. Print.
