Fundamentals of Quantitative Research

Quantitative tools gather numerical and statistical data using experiments, measurements, fixed-response questionnaires, test scoring, et cetera. The approach is underpinned by 'scientific ' world views of cause and effect, belief in the objectivity of the researcher and the search for truth. Quantitative methods used in library assessment include web server statistics, electronic counters and surveys. These surveys are usually questionnaire-based and, at their best, are grounded in extensive and on-going piloting which uses qualitative methods such as focus groups and individual interviews to establish that the questions are meaningful to the user community. They often employ empirical testing, which targets specific groups and topics while also fulfilling the scientific 'trinity of validity, generalisability, and reliability ' (Janesick, 2000, p393) (Haynes, 2004)

Characteristics of A Quantitative Problem Statement
The statement of the problem must first be expressed with the utmost precision; it should then be divided into more manageable subproblems. Such an approach clarifies the goals and directions of the entire research effort. (Leedy and Omrod, 2010)

Formulation of Quantitative Research Questions and Hypotheses
The process of forming and testing a hypothesis (i.e., a theory) is as follows: 1. Determine an appropriate expected outcome based on theory and experience. This is generally referred to in inferential statistics as a “research hypothesis.” 2. Formulate a pair of testable hypotheses related to the research hypothesis: a “null hypothesis” and an “alternative (research) hypothesis.” The testable hypotheses must be mutually exclusive and collectively exhaustive. The hypothesis testing goal is to falsify or reject the statement of truth implied by the null hypothesis, leaving the research hypothesis as the only reasonable alternative. 3. Formulate a conclusion that falsifies (or fails to falsify) the null hypothesis.(Wolverton, 2009)

Procedures of Quantitative Data Collection
In quantitative research, the intent of sampling is to choose individuals that are representative of a population, so that results can be generalized to it (external validity). To accomplish this task, quantitative researchers may resort to both probabilistic (i.e. each member of the population has the same probability to be included in the sample) and purposive (i.e. use of some criterions to replace the principle of canceled random errors). In quantitative research, data has to be collected which are relevant to test the formulated hypotheses. Data collection is attained by using tests or standardized questionnaires (which assess performances, attitudes, personality, self-perception, etc.), structured interviews (where the interviewer just reads the pre-defined questions and records the answers related to one or more issues or phenomena relevant to the research questions), and closed-ended observational protocols (which allow classifying the behaviour of interest using pre-defined categories). Secondary data may also be collected as, for example, referring to official documents (e.g. financial records and census data). The resulting data is finally coded by assigning numeric values, and successively introduced into a data matrix, which will be used for the statistical analysis. (Gelo, Braakman & Benetka, 2008)

Procedures of Quantitative Data Analysis
All research activity is subordinate to the research problem itself. Sooner or later, the entire effort must result in an interpretation of the data and a setting forth of conclusions, drawn from the data, to resolve the problem being investigated. Inexperienced researchers sometimes forget this. Activity for activity’s sake is seductive. Amassing great quantities of data can provide a sense of well-being. Like Midas looking at his hoard of gold, researchers might lose sight of the ultimate demands that the problem itself makes on those data. Presenting the data in displays and summaries—graphs, charts, tables—does nothing more than demonstrate the researcher’s acquisitive skills and consummate ability to present the same data in various ways. Descriptive research ultimately aims to solve problems through the interpretation of the data that have been gathered. (Leedy and Omrod,2010)
References
Gelo, O., Braakmann, D., & Benetka, G. (2008). Quantitative and Qualitative Research: Beyond the Debate. Integrative Psychological & Behavioral Science, 42(3), 266-290. doi:10.1007/s12124-008-9078-3.
Haynes, A. (August 2004). Bridging the gulf: mixed methods and library service evaluation. The Australian Library Journal, 53, 3. p.285(22). Retrieved February 15, 2010, from General OneFile via Gale: http://proxy.montgomerylibrary.org:2061/gtx/start.do?prodId=ITOF&userGroupName=rock21695 Leedy, P. D. & Ormrod, J. E. (2010). Practical research: Planning and design (9th ed.). UpperSaddle River NJ: Pearson
Wolverton, M. (2009). Research Design, Hypothesis Testing, and Sampling. Appraisal Journal, 77(4), 370. Retrieved from MasterFILE Premier database.

References: Gelo, O., Braakmann, D., & Benetka, G. (2008). Quantitative and Qualitative Research: Beyond the Debate. Integrative Psychological & Behavioral Science, 42(3), 266-290. doi:10.1007/s12124-008-9078-3. Haynes, A. (August 2004). Bridging the gulf: mixed methods and library service evaluation.  The Australian Library Journal, 53, 3. p.285(22). Retrieved February 15, 2010, from General OneFile via Gale: http://proxy.montgomerylibrary.org:2061/gtx/start.do?prodId=ITOF&userGroupName=rock21695  Leedy, P. D. & Ormrod, J. E. (2010). Practical research: Planning and design (9th ed.). UpperSaddle River NJ: Pearson Wolverton, M. (2009). Research Design, Hypothesis Testing, and Sampling. Appraisal Journal, 77(4), 370. Retrieved from MasterFILE Premier database.