When creating a research design, it is important to decide what methods you are going to use to collect data. There are two main types of research methods: qualitative and quantitative. Scientists debate on the effectiveness of each type as a way to record data. By weighing the pros and cons of qualitative and quantitative research, you can select the best method for your study.
Advantages of Qualitative Research
Qualitative research if often implemented as an exploratory form of data collection at the start of a research project. A researcher makes subjective recordings, descriptions or sketches on what is going on during an observation. Qualitative data can give the researcher a better idea of what to look more closely at for later trials. This type of data often contains more substance than quantitative methods because the researcher can take into account the experiment's context or bigger picture.
Disadvantages of Qualitative Research
Qualitative research methods become less useful during later portions of a study, especially when trying to test hypotheses. The data is subjective, meaning it is in the opinion of the researcher whose judgment could be variable. It is difficult for someone else to try and duplicate a study based on qualitative data. For example, a mixture that is blue to one person might look more like green to someone else. Trying to explain how the measures were taken might require more effort than the study itself.
Advantages of Quantitative Research
Quantitative research focuses its attention to numeric qualities that can be recorded. Weight, size and time are examples of quantitative measurements. Because they are standardised, quantitative measurements are objective and can be duplicated by other researchers. It is best to use quantitative methods in the latter phases of a research project, when you know exactly what you hope to find. With quantitative data, you can test your hypothesis and make general conclusions.
Disadvantages of Quantitative Research
A disadvantage of quantitative methods is that it can be difficult to provide context within your results. For example, you can quantify the ticket sales of a movie premiere, but that information does not help you know if the movie was good or bad. Quantitative data often feels colder or more detached than qualitative measures; therefore, while quantitative data can prove a hypothesis and draw conclusions, it cannot always give meaning to what is being examined.