The quantitative research means the researcher collects numerical data and evaluates the data with the use of financial software such as SPSS and Microsoft Excel Spreadsheets. The quantitative research involves testing the hypothesis that is derived from the theory that is being tested. The research questions are determined and according to these questions; the participants undergo different research methods. If the main purpose is to generalize the theory from the participation of participants, the research will use probability as sampling to select the participants.
Three sampling methods with advantages and disadvantages
Random sampling
The random sampling method is the least biased of all the sampling techniques that will be discussed further. There is no subjectivity involved in this sampling technique. This means that each member of the population that is involved in sample has an equal chance of being selected through random sampling process. The random sample can be accessed with the use of random number tables – a function that is available in Microsoft Excel. The advantage of using random sampling is that it avoids bias as the sample is selected randomly, and it can be used with large population sample. The disadvantage of random sampling is that it can lead to poor representation of the overall population as the participant is selected through random numbers that are a generation. Another disadvantage is that it may involve certain time and study area limitations and restrictions (Cohen, 2000).
Systematic Sampling
Unlike the random sampling, the samples are selected in a systematic way. This involves the presentation of sample at regular intervals or regular numbering of the sample, for example, every 20th house or an individual. The advantage of this sampling method is that it is clear and straightforward, unlike the random sampling method. Second, the samples can be situated at regular intervals and third, a good coverage is given to the total population, unlike the random sampling technique. On the other hand, the disadvantage of this technique is that it more biased and not all the members will have an equal chance of being selected and there is a chance of over or under-representation of the population (Cohen, 2000).
Stratified sampling
This sampling technique is used when the main parent population is made up of subsets of pre-determined sizes. These sub-sets are designed in a manner that they make up different sections of the total population that will require the stratification of the sample. The advantage of using this sampling technique is that it can be used with both systematic and random sampling method. If the correct proportions are used of the sub-sets, it can eventually generate better results than other techniques. Third advantage is that this technique can be applied at various areas. The major disadvantage of this technique is that it is imperative that correct proportions of the sub-sets should be used in order for it to work properly and second that a lot of hard work is required to design questionnaire based on stratified sampling (Cohen, 2000).
Three quantitative research methods
Survey
Survey is an extremely popular quantitative data collection method especially when the information gathering requires assessing large groups of participants and where the standardization of the survey process is significant. There are many different ways to construct the surveys, but a survey program constitutes of two major components – the questions and the responses to these questions. Even though sometimes the researchers try to keep the responses open-ended but it is imperative that in quantitative research the shift and focus should be towards close-ended surveys that enable the respondents to answer the pre-determined answers. This makes it easier to code the response, is less costly and requires lesser time and resources to handle the close-ended survey questions. In the survey, questionnaire is developed using a rating scale, might involve certain percentage categories of how the participants might get involved in a certain activity (Kothari, 2011).
Structured Interviews
The use of a structured interview is another quantitative research method. The main purpose of conducting an interview is that the perspective that the participants will present is meaningful and can be explicit. It is imperative to note that the comments and perspective of the participants will help in achieving the success of the project. The use of a structured interview is important because it involves proper administration of the questionnaire with immense care in wordiness of the questions (Kothari, 2011).
Tests
Test is another quantitative research method that involves testing the knowledge and capability of the participant and his capacity to apply the subject knowledge in new situations. These tests can take many forms – the participants can be required to choose from different alternatives available such as selecting the best available answer, selecting the correct answer, or selecting an incorrect answer, to write short answers to the questions available or to elaborate on the questions and provide a comprehensive answer.
When to use the quantitative research instruments
The surveys are used when it is required to collection information from the large number of people, and the answers are required for close-ended questionnaire that helps in providing crisp and to the point responses. This quantitative research method is considered an effective tool in obtaining responses on a wide array of subjects and can be used when the in-depth responses are not required from the respondents. At times, the organizations use the same survey again and again with intervals in order to evaluate and analyze the progress of a certain task. An interview can be used at any stage of the research especially a structured interview. On the other hand, tests are used when the researchers want to evaluate the current stage of knowledge or if any change has occurred in prior knowledge of the subject. The change in results of the test will determine, whether the project has been successful still needs improvement or has completely failed to achieve its main purpose (Kothari, 2011).
Statistical methods – Descriptive and Inferential
Descriptive statistics
The descriptive statistics involves analysis of the data that will help to show and summarize the data in a way that is meaningful, and the data can be interpreted well in the way it is presented. The descriptive statistics is a way to analyze our data and does not provide any conclusion or recommendation to the analysis. This statistics method is important because if we leave the data raw it will be hard to interpret it (Cohen, 2000).
Inferential statistics
The inferential statistics unlike the descriptive statistics not only help in analyzing and describing the data but also in drawing effective conclusions to the analysis. Both the methods can be used as a mixed approach, and the outcome of the analysis will be as desired. Through descriptive statistics, the data can be analyzed and described and with the help of inferential statistics the data that is described in the above method can be used to reach a conclusion. In my organization the mixed approach is appropriate as only data description and analysis will not play its role, it is imperative that conclusions are reached (Cohen, 2000).
References
Cohen, L., Manion, L. & Morison, K. (2000) “Research Methods in Education (5th edn) (Routledge Falmer).
CR Kothari (2011) “Research Methodology: Methods and Techniques” New Age International.
