Measurement Scales in Science - Research Paper Example

TABLE OF CONTENTS I. Scientific Research ………………………………………………………………………..3 II. The Purpose of Literature Review in Survey Research ……………………………….…5 III. The N-O-I-R Data Measurement Scales ……………………………………………….. 6 IV. The Standard Normal Curve …………………………………………………………….8 V. The Importance of Cross-tabulation in Survey Monkey ………………………….………9 VI. References ……………………………………………………………………………...10 I. Scientific Research Scientific research is a structured methodological approach in application of scientific methods to answer questions and prove conclusions. Scientific research provides a way for understanding and appreciation of the things naturally occurring around us. It is our way of finding out facts that explain logical reasons of certain events. It is also a method of answering our queer minds about its interests in our environment. This allows us to make sense on how things work and why some things look or act the way they do. Scientific research has allowed our advancement as human species in this world. It enabled our superiority and survival among other organisms that inhabit the planet. Through scientific methods of inquiries, observations, experimentations, data analyses and continuous approaches of data verifications, several answers to essential survival needs have been known and developed further for mass benefits. This includes scientific breakthroughs in medicine, human anatomy, diseases, ecology, astronomy, society and various phenomenon relating to humanity and our survival in our environment. It is to be noted that scientific research does not provide absolute answers to questions (Ori 2012). It instead provides answers based on the current knowledge acquired and recent evidences from what is present. That is why asking the right questions and formulating sensible hypothesis from current sources of information, are critical to advance our existing knowledge. The solutions that we have right now, the technologies we are enjoying and existence of rich data sources are product of all the efforts of scientific research in the past. There are more cures to sicknesses right now because researchers from the past have already discovered these solutions. The sophisticated technologies we are using in computers and network systems are result of the development of information technologies and facets of circuitries, with applications of social sciences and human response mechanisms. It generally means that the questions that have been asked before have been answered in this generation. Thus, whatever questions and challenges we have in our present time, these will be important on how the future will be shaped. The accumulation of knowledge and its by-products continuously happen, and more discoveries are being known. These are the driving mechanisms on the advancements that are yet to occur in the time to come. Conducting scientific research in the light of scientific methods is critical to the validity of results. Validity of conclusions is important to be proven. Ideas can be accepted or rejected based on the adherence to the scientific standards and measures. This information process or scientific system helps provide consistency on how data are acquired and collected. If proven valid and accepted, the discovery can be adapted as a scientific paradigm that could be used as a sound reference of science. In here, it could be supporting other already existing paradigms that then bring to unification of ideas, and therefore establish our understanding of that scientific matter. If this is achieved, the system could be used in application of product development or systems design. This is when solutions are created or developed, and innovations that improve what we currently have are appreciated. Scientific research entails repetition and accuracy of scientific method applications. It is also vital that the results are written in the form of publications, so that other people in the field could be informed about it and verify its validity. Peer reviews on the written report or publication provide rooms for improvements on the scientific research. This is the method how researchers around the world interact and, help and build up each other for the benefit of scientific community and its stakeholders. II. The Purpose of Literature Review in Survey Research Literature review is a written body of text that accounts what already has been published about the topic as contributed by other researchers (Taylor n.d.). Literature review describes the scientific discoveries that have been done which are relevant to the research that is going to be conducted. This allows the researcher to be in a good perspective on how his research can be done appropriately in light of all the knowledge that has already been acquired about the topic of interest. It therefore prevents redundancy of repeating something that has been proven correct or incorrect already. It also enables the researcher to determine the gaps in knowledge by finding out what areas still need to be studies in his topic. It then allows advancement in the area of study, as the researcher appropriate his objectives and methods according to the current status of research in his subject. Survey research is “one of the most important areas of measurement in applied social research which encompasses any measurement procedures that involve asking questions of respondents” (Trochim 2006). It provides a good assessment of how people think about or feel about a particular subject. Thus, analyses and evaluations of a social topic can be drawn from a valid source of information. This method of research consists of predetermined sets of questions that are to be asked to a group of people called sample. In doing such, the researcher collects information from a population that comes from his sample. Depending on what the researcher is trying to find out, survey research enables him to answer those questions through a collective answer from his sample set. Literature review in survey research provides an understanding on where the focus of the research must be. It enables the researcher to support the research that he is going to embark by laying out all the facts from previous discoveries relevant to his topic. This provides credibility on the topic of research, that it is indeed significant and answers are needed to be sought, as proven by others, who before him have initiated conducting research on the topic. Literature review must be conducted on a survey research when it is required to strengthen why the research is being done and why the survey methods were chosen as the scientific methodology to answer specific questions. Through literature review, the researcher can cite what the established authors in his field have said. This is a good approach to prove the scientific relevance of the social research to be conducted, on the basis of the thoughts that other researchers have spent on the topic. The citing of past research or the referencing method acknowledges the scientific method already performed by the researcher upon commencing his literature review, which is inquiry. It meant that the researcher has done responsible inquiring or investigating about his topic, and that it is not a mere random selection of subject. Therefore, a scientific basis is established on the grounds of the survey research. III. The N-O-I-R Data Measurement Scales The typical assignment of numbers to various attributes of people, objects or concepts or simply the process of measurement is typically done in many areas of science, especially that of social science. This is done in order to allow analyses and evaluation on the area being studied in a population or subject. In Statistics, the four levels of measurement recognized are nominal (N), ordinal (O), interval (I) and ratio (R). Each of these is explained further below. Nominal (N) With this measurement scale, there is no relative ordering of the categories or the assigning of numeric scores to each category is purely arbitrary (Measurement Scales in Social Science Research 1999). The Nominal Measurement Scale is used for variables that must be grouped into one mutually exclusive and exhaustive category. Example: Categorizing the participants in a study as “male” and “female” refers to “gender” as a measurement on a nominal scale. Ordinal (O) Ordinal measurement scale informs us of the order or relative position of subjects being measured. Although it doesn’t tell us anything about absolute magnitude of the difference between these orders. We just know that they are measured by this ordinal scale of order. Example: Report card marks of “A”, “B”, “C”, “D” and “E” informs us of how well the student met the standard of requirements in a school grading system. It gives us the order of school performance measurement, of which “A” is excellent and the next level in the order means diminishing performance. Interval (I) The interval measurement scale provides a distance or difference between numbers or units on the scale. It means that data can be ordered and the difference between data values has meaning. Example: Temperatures are measured in Fahrenheit (F), and intervals or the distance between temperature measurements have values or meanings. Ratio (R) The ratio measurement scale provides a natural zero as the starting point. It means that the numbers or units on a scale are equal in all levels of the scale, and that the natural zero starting point allows interpretation of ratio comparisons. Thus, the differences and ratios would have meaning. Example: A very good example of ratio measurement is time. The difference between the time of 5 hours and 10 hours are the same in that they have equal intervals. We can also say that 10 hours is twice as long as 5 hours (now a ratio comparison). IV. The Standard Normal Curve A standard normal distribution or curve refers to a normal distribution that has a mean 0 and a standard deviation of 1 (see Figure 1). This is a part of introductory statistics. Areas that are under the normal distribution are found using a standard normal table. However, in our experimental measurements of variables, none of them would possess a perfect normal distribution. Although, all other distributions are equivalent to this distribution when we change the unit of measurement to standard deviations from the mean. Hence, the normal distribution is important so that we can use it as a reference especially when we deal with analysis that involves normal distribution (The Standard Normal Distribution n.d.). Figure 1. Standard Normal Curve (The Standard Normal Distribution n.d.) The normal distribution graph above (Figure 1) is dependent on two factors – the mean and the standard deviation. The mean of the distribution is the one that determines the location of the graph’s centre while the standard deviation defines the height and the width of the graph. If the standard deviation is big, the curve appears short and wide. When it is small, then the curve is tall and narrow (Normal Distribution Curve 2010). All normal distribution curves are symmetric and bell-shaped as shown in Figure 1. In summary, it has the following characteristics (based on Normal Distribution Curve 2010): 1. The normal curve is a symmetric bell-shaped curve. 2. 50% of the scores lie above and 50% below the midpoint of the distribution. 3. The total area under the curve is equal to 1. 4. Curve is asymptotic to the x axis. 5. Mean, median, and mode are equal and located at the midpoint of the x axis. V. The Importance of Cross-tabulation in Survey Monkey Cross-tabulation in Survey Monkey is useful in comprehending information from two different survey items. The crosstab tool enables interrelation of collected data that are from two different sources. It is actually a matrix of two or more data sources tabulated against each other, such that the data of one item can be quickly compared to the data of the other item. It helps in quickly spotting related data or relationships from the data presented. Likewise, if there are no relationships or connections on the survey data collected, a crosstab approach in Survey Monkey can easily reveal the result. Thus, the cross-tabulation provides an experimental method to visually process the survey data. It allows data mining and exploring relationships between survey items. This is an essential part of scientific research categorized in hypothesis formulation and data analysis. Looking through data relationships, where there are strong points and weak points, is the scientific process done through cross-tabulation. It helps researchers to find out whether there are differences or not in the factors or survey questions being compared (Bhate 2011). The answers are then backed up by the statistics exhibited by the numerical projection of the results. This is a critical part as it can prove the significance of the research conducted. It also establishes whether the data collection method was done accordingly. It enables further exploration on the quality of how the research was implemented and whether the basis of such proves a strong argument in the scientific community. VI. References Bhate A 2011. Cross Tabulation in Survey Analysis. ArticleSnatch LLC. Retrieved from http://www.articlesnatch.com/Article/Cross-Tabulation-In-Survey-Analysis/582398#.UJzSN4cm2Jo. Measurement Scales in Social Science Research 1999. SABLE. Retrieved from http://simon.cs.vt.edu/SoSci/converted/Measurement/ Normal Distribution Curve 2010. TutorVista.com. Retrieved from http://math.tutorvista.com/statistics/normal-distribution.html# Ori J 2012. Importance of Scientific Research. eHow: Discover the expert in you. Retrieved from http://www.ehow.com/about_6137969_importance-scientific-research.html Taylor D n.d. What is a review of the literature? University of Toronto. Retrieved from http://www.writing.utoronto.ca/advice/specific-types-of-writing/literature-review The Standard Normal Distribution n.d. Retrieved from http://www.oswego.edu/~srp/stats/z.htm Trochim WMK 2006. Survey Research. Research Methods: Knowledge Base. 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