In research, measurement is the series of actions or methods researchers use to observe and record the information collected as part of a study. Therefore, in order to understand measurement the researcher much understand the basic ideas entailed in measuring, such as the stages of measurement that help the researcher decide how to make sense of data from particular variables in a study as well as the reliability of the measurement. An understanding of the different types of measurement is important in any research endeavor (Research methods knowledge base, 2006).
One of the categories of measurement that researchers find difficult to understand is called scaling. Trochim and Donnelly (2008) define scaling as “the branch of measurement that involves the construction of a measure based on associating qualitative judgments about a construct with quantitative metric units” ( p. 129). Similar to an index, which applies a measurable score formulated by applying a set of standards to connect variables in order to reflect an acceptable research design, a scale is constructed to render...
In response to the question set, I will go into detail of the study, consisting of the background, main hypotheses, as well the aims, procedure and results gathered from the study; explaining the four research methods chosen to investigate, furthering into the three methods actually tested.
There were many measurement formulas taken under considerations within the investigation in order to study the given topic question. These formulas played a significant role in solving the topic question and the main ones considered were –
Quantitative research methods include information having numeric meaning, also measuring. Focus in this research strategy is on measurement and the comprehension of the relationship amongst variables (Lincoln, 2003). Quantitative analysis consequently depends and builds on statistical trials, for example frequency, mode, median, quantity and arithmetical procedure.
Quantitative investigation approaches attempt to exploit objectivity, replicability, and generalizability of answers, and are characteristically interested in forecast. Integral to this approach is the hope that an investigator will set aside his or her involvements, perceptions, and prejudices to ensure impartiality in the behavior of the study and the deductions that are drawn. Key topographies of many quantitative educations are the use of tools such as tests or reviews to collect data, and dependence on likelihood theory to test statistical premises that correspond to research queries of
The father of quantitative analysis, Rene Descartes, thought that in order to know and understand something, you have to measure it (Kover, 2008). Quantitative research has two main types of sampling used, probabilistic and purposive. Probabilistic sampling is when there is equal chance of anyone within the studied population to be included. Purposive sampling is used when some benchmarks are used to replace the discrepancy among errors. The primary collection of data is from tests or standardized questionnaires, structured interviews, and closed-ended observational protocols. The secondary means for data collection includes official documents. In this study, the data is analyzed to test one or more expressed hypotheses. Descriptive and inferential analyses are the two types of data analysis used and advance from descriptive to inferential. The next step in the process is data interpretation, and the goal is to give meaning to the results in regards to the hypothesis the theory was derived from. Data interpretation techniques used are generalization, theory-driven, and interpretation of theory (Gelo, Braakmann, Benetka, 2008). The discussion should bring together findings and put them into context of the framework, guiding the study (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). The discussion should include an interpretation of the results; descriptions of themes, trends, and relationships; meanings of the results, and the limitations of the study. In the conclusion, one wants to end the study by providing a synopsis and final comments. It should include a summary of findings, recommendations, and future research (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). Deductive reasoning is used in studies...
Scale of measurement is used to categorize and define numbers and variables in both quantitative and qualitative manner. There are four (4) scales of measurement : (Nominal, Ordinal, Interval, Ratio) which were used depending on the information that the data is intending to represent. Each scale tends to represent specific kind of information.
The most popular method of quantitative research is an experiment, which gives casual information and hard numbers (Guts, 2014). Experiments are easy to understand, and provide accessible information that helps predict human behavior (Guts, 2014). In experiments, researchers manipulate variables using experiment and control groups. (Guts, 2014). An experiment includes independent and dependent variables. An independen...
Unlike Present Day, where most scientific groups and people use the standard unit of measurement; the metric system, there used to be a time when a variety of units of measurement were frequently used throughout the world, some units were also measured using the human body. For example length could be measured in numerous ways such as feet, hands, cubits, palms, rods, furlongs and many more. This creation of multiple varying units created an absence in common measurement standards, leading to a lot of misunderstanding and a significant drop of efficiency in the trade between countries. This havoc remained persistent until the eighteenth century when those countries had learnt that “United We Stand; Divided We Fall”-Aesop.
Quantitative research uses a deductive reasoning also known as top to bottom or (top down approach) starting with a theory, then the hypothesis, followed by observation and finally confirmation , going from the general to the more specific. Quantitative methods use numbers and statistics to show the results of the research exercise and mainly are concerned with mathematics and statistics. In quantitative research there are levels of measurement being firstly nominal which are names of things followed by ordinal sequence of things, interval where the sequence has equal distance between each item, and ratio where there is a true zero (Alston & Bowles, 2003, p. 7-9).
Earlier article (University of Paisley 1997) defined approaches to research primitively using these two simplest words helped presenting a good contrast between differing schools of thought. If in a research the emphasis of data collection is on the quality rather than the quantity, it is qualitative. However, when the research is of “quantitative orientation”, data collection focuses on some form of factual relationship.
The development of knowledge requires a number of processes in order to establish credible data to ensure the validity and appropriateness of how it can be used in the future. For the healthcare industry, this has provided the ability to create and form new types of interventions in order to give adequate care across a of number of fields within the system. Research then, has been an essential part in providing definitive data, either by disproving previous beliefs or confirming newly found data and methods. Moreover, research in itself contains its own process with a methodological approach. Of the notable methods, quantitative research is often used for its systemic approach (Polit & Beck, 2006). Thus, the use of the scientific method is used, which also utilizes the use of numerical data (Polit & Beck). Here, researches make use of creating surveys, scales, or placing a numerical value on it subjects (Polit & Beck). In the end the resulting data is neutral and statistical. However, like all things its approach is not perfect, yet, it has the ability to yield valuable data.
Traditional research may use quantitative or qualitative research method. According to Hendricks (2009), quantitative research is a general conclusion based on hard data. Hen-dricks describe quantitativ...
Theory in quantitative research is the use of an interrelated set of constructs (or variables) formed into propositions, or hypotheses, that specify the relationship among variables (typically ...
Quantitative research involves the collection and converting of data into numerical form to enable statistical calculations be made and conclusions drawn. It provides a measure of how people think, feel or behave and uses the statistical analysis to determine the results. However, this measurement results in numbers, or data, being collected, which is then analyzed by using quantitative research methods (Byrne, 2007).
Quantitative research is guided by the positivist paradigm. This is what many people believe and are taught is the method of “real science”. This paradigm seeks to collect data that can be ordered, categorized and graphed. Positivism is most concerned with the reliability, validity, and generalizability of the knowledge. This method begins with a theory. Using deductive logic, a testable hypothesis is formulated. Data is then collected and complied to test this theory (Bailey, 2007, p. 52). Quantitative research places immense importance on the neutrality of the researcher. It is crucial for the quantitative researcher to maintain a value-free approach in order to avoid influencing their results. It is believed that anything less allows for bias on the part of the researcher and subsequently, tainted results. The final product of research is supposed to hold no evidence of reaction to its findings. T...