Research Methods and Statistics - Essay Example

Statistics and Quantitative Research A considerable number are in agreement that statistics is the art and science of collecting, presenting, analyzing and interpreting data (Bryman, 2008; Seale, 2004). Quantitative research on the other hand pertains to numerical analysis in order to quantify information and gather enough evidence to come up with considerable conclusion based on quantitative analysis (Bryman, 2008). Depending on how one uses it, statistics connotes different meanings. At some point, it can be said that statistics is to the sample while parameter is to the population. Some believe that it is an estimate, a measure or data. Considering it as a subject, statistics consists of two major functions: descriptive and inferential statistics. Descriptive statistics is about collection and presentation of data, as well as describing the characteristics of individual objects or groups of individuals under study (Donnelly, 2004). Some of the descriptive statistics which are commonly used are the frequency distribution, like tables, graphs, figures. Other measures that can be used in describing the characteristics of individuals or groups of individuals or objects under study are the measures of dispersion and whether the data has normal or abnormal distribution. Inferential statistics on the other hand is about the analysis and interpretation of data (Donnelly, 2004). This statistics consists of different statistical tools/tests used in the analysis of the interval, ratio, nominal and ordinal data. These tests are used in making inferences from or conclusions on larger groups, and populations, or in making generalizations about them on the basis of information obtained by the study of one or more samples. The extent to which the use of this statistics can be done with accuracy depends on the goodness of samples. The sampling techniques or procedures are also of great importance with regard to the use of these different statistical tests. Empirical studies and statistical studies are said to be categories where quantitative research falls and quantitative methods have become integral parts. In these, control of variables, randomization, reliable measures and generalization from the sample to the population are taken into consideration (Newman and Benz, 1998). Today, psychology, social science, epidemiology, education, economics, public health and marketing are some of the major fields trying to make use of the advantages of quantitative research (Kumar, 2005). These fields normally require investigating the relationship between observed phenomena and chosen variables. Quantitative research can provide further explanations or details of any relationship that might be determined from the tested variables by the investigator (Creswell, 2003). As stated earlier, statistical studies are categories of quantitative research. It is a common observation that a quantitative research using statistical study may either employ descriptive statistics, inferential statistics or even both of them. It is therefore implied that the use of statistics at some point is an integral part of quantitative research. This is evident enough when the researcher is trying to employ in his or her study quantitative data, but the method to be employed does not necessarily follow to be in line with quantitative research (Taylor et al., 2006). This is due to the fact that from the point of view of the researcher there are some considerable choices at hand and subject matters to be taken into account. References Bryman, A. (2008) Social Research Methods. 3rd ed. Oxford: Oxford Universiy Press. Creswell, J. W. (2003) Research design: qualitative, quantitative, and mixed methods approaches. USA: SAGE. Donnelly, R. A. (2004) The complete idiot’s guide to statistics. USA: Penguin. Kumar, R. (2005) Research methodology: a step-by-step guide for beginners. Malaysia: SAGE. Newman, I., and Benz, C. R. (1998) Qualitative-quantitative research methodology: exploring and interactive continuum. USA: SIU Press. Seale, C. (2004) Researching Culture and Society. 2nd ed. London: SAGE. Taylor, B., Sinha, G., and Goshal, T. Research Methodology A Guide For Researchers In Management And Social Sciences. New Delhi: PHI Learning. Surveys and Questionnaires Surveys are specific methods or a series of process normally used to gather important data from chosen respondents or groups in order to obtain the necessary information for the study (De Vaus, 2002). Questionnaires on the other hand are common tools used in the survey and it is therefore necessary to take time perfecting the questions or information found in them (De Vaus, 2002). Conducting surveys is very important process to studies trying to investigate information from chosen respondents. Surveys are usually done using personal interview through phone or casual interview with the respondent or group of people. Survey nowadays can also be conducted online through emails or via internet (De Vaus, 2002; Bryman, 2008). As the usual way, survey can also be conducted through the use of questionnaires which are used as the traditional way of collecting data. From the perspective of quantitative research methodology, survey is a matter of choosing samples from a chosen population. The data obtained from these samples can be representative enough to describe the entire population provided that there is a higher significance of information and number from the chosen samples (Kalton, 1983). Survey is a way of gathering significant information in order that a certain study can be successfully implemented with results or significant conclusions. Survey seems so easy to be implemented but there are various considerations to be taken into account. For instance, if the questions involved seem to be confidential or the respondents are not comfortable to answer them, a higher possibility that the information that can be obtained from the survey may be distorted at some point. In this case, the survey itself does not make sense at all. In this case, there is a need to reconsider better ways to successfully implement effective survey with the chosen respondents. Survey is an integral part of every a study and in order to come up with reliable results, it has to be properly designed beforehand and the use of advanced technology might help but other challenges may be remarkable (O’Carroll, 2003). Usually surveys try to employ questionnaires in order to gather data and reliable information. These two should come together. Surveys involving questionnaires cannot be conducted without the use of the latter. In this case, these two are dependent with each other. Thus, the right method of survey should be implemented in order to maximize the potential of questionnaires. In the same way, the right questions on the questionnaires should be taken into account prior to effective implementation of surveys. In short, surveys and questionnaires should come together in good quality standard in order to obtain the right data that can be processed as the right information (De Vaus, 2002). The questionnaires must contain questions that are of greater relevance with what the researcher is trying to obtain at the end of the study. Questionnaires must be in line with the objectives of the study. It is through these questions within the questionnaires that the objectives of the study will be essentially addressed provided that relevant information can be obtained from the respondents. In the case of confidentiality and some questions in which respondents are not comfortable to disclose information or their stand, the quality of information cannot be guaranteed. References Bryman, A. (2008) Social Research Methods. 3rd ed. Oxford: Oxford Universiy Press. De Vaus, D. (2002) Surveys in Social Research. 5th ed. London: Routledge. Kalton, G. (1983) Introduction to survey sampling. USA: SAGE. O’Carroll, P. W. (2003) Public health informatics and information systems. USA: Springer. Quantitative Data Analysis Quantitative data analysis is a specific process that tries to find out value or meaning from obtained set of quantitative data based on the underlying research process of a certain field (Seale, 2004; Bryman, 2008). In short, quantitative data analysis is a numerical examination and interpretation of observation (Babbie, 2008). As part of any quantitative research methodology, quantitative data analysis is a significant process to be taken into consideration. There are different areas of expertise and each of them carries a research process which carries corresponding type of data analysis. Quantitative data analysis therefore should fit into the research process involved in a certain field (Bryman and Cramer, 1990). This means that prior to the analysis of data; collection of them must be initiated through survey or experimental design but the entire basis must be in line with the involved theoretical domain (Bryman, 2008). The point of this is to emphasize that the type of data analysis involved in any research process must be initiated in such a way it is in line with the discipline of the corresponding field. The quantitative data analysis can be both implemented in the analysis of data from survey and experimental design for as long as the data involved are all quantitative in their nature (Bryman and Cramer, 1990). A large portion of empirical research is designed to come up with quantitative data (Bryaman and Cramer, 1996). It is because of this consideration that there is a need to essentially understand quantitative data analysis as a technique in analyzing data and transforming them as useful information. The transformation involved in here carries the big portion of examination and interpretation of observation. However, the whole process is done in numerical manner since this is about quantitative data analysis. The most commonly used analysis tool in this aspect is statistics which involves inferential and descriptive means of examining and interpreting data (Donnelly, 2004). However, it is on the inferential part where there are more sophisticated analyses and depth interpretations of data. In this case, as commonly observed especially on studies in social science, mostly inferential statistics are employed when for instance the goal is to determine any relationship among the variables and observations involved (Bryman, 2008). Quantitative data analysis is a powerful tool to extract relationship and relevant information in order to come up with significant information in the study. Even though qualitative data analysis is very common, quantitative data analysis proves to be a powerful part of a research process. It is through this process that the importance of numerical observation is proved to be crucial in coming up with significant interpretation of data. Facts and figures are relevant information and some of them can be processed by employing quantitative data analysis. A research process relying on quantitative data analysis is therefore treating numerical examination and interpretation as primary moves prior to reaching the final numerical facts and figures of the entire research process (Bryman and Cramer, 1990). This proves that quantitative data analysis is an integral part of the whole research process and its value cannot be taken for granted considering that the final output is to integrate information based on processed quantitative information. References Babbie, E. R. (2008) The basics of social research. USA: Cengage Learning. Bryman, A. and Cramer, D. (1996) Quantitative data analysis with minitab: a guide for social scientists. New York: Rouledge. Bryman, A., and Cramer, D. (1990) Quantitative data analysis for social scientists. New York: Taylor and Francis. Bryman, A. (2008) Social Research Methods. 3rd ed. Oxford: Oxford Universiy Press. Donnelly, R. A. (2004) The complete idiot’s guide to statistics. USA: Penguin. Seale, C. (2004) Researching Culture and Society. 2nd ed. London: SAGE. Read More