Introduction
If you are looking for scientific proof, then validity and reliability are what you need. In the work by Xie, & Huang (2014) they describe the following:
The principles of reliability and validity are fundamental cornerstones of the scientific method. Reliability is defined as the extent to which a measure is repeated under ideal conditions. Validity refers to the degree to which a test measures what it purports to measure. Establishing good quality studies need both high reliability and high validity. (p.326). Both of these concepts are worthy of exploration, and understanding them is crucial for evaluating, designing, and performing scientific studies.
Reliability
Reliability is about consistency. For data to have reliability, it will need stability, internal reliability, and inter-observer reliability.
Stability. If a measure does not fluctuate over time, it is considered to have stability. Data collected at one period of time and then collected again at a different period in time will not have a great deal of variability. Stability can be tested by administering a test at one point in time and then re-administering the same test under the same conditions.
Internal Reliability
Internal reliability. This refers to the scale that is used to measure data. If the scale is consistent, then it is said to have internal reliability. We need to be sure that whatever variation we are measuring is actually produced by the variables, not by the
Relaible measurment is the consistency of a set of measurements or of a measuring instrument, often used to describe a test. Reliability is inversely related to random error. The validity of a measurment is how accurate it is. Reliability does not imply validity. That is, a reliable measure is measuring something consistently, but you may not be measuring what you want to be measuring. For example, while there are many reliable tests of specific abilities, not all of them would be valid for predicting, say, job performance. A common example often used to illustrate the difference between reliability and validity in the experimental sciences involves a common bathroom scale. If someone who is 200 pounds steps on a scale 10 times and gets readings of 15, 250, 95, 140, etc., the scale is not reliable. If the scale consistently reads "150", then it is reliable, but not valid. If it reads "200" each time, then the measurement is both reliable and valid. This is what is meant by the statement, "Reliability is
Consistency - Leads to reliability we mean what we say. We are consistent in our dealings with people, product, price and all other aspects of our day to day professional life.
Validity refers to whether the research conducted is what it intended to be. Validity involves dependability, which means, a valid measure must be reliable. But, reliability doesn’t have to link to validity, a reliable measure is not required to be valid.
The verification principle is known to be one of the most discredited and flawed theories of the 21st century. The major flaw
|What criterion must be met |Consistency: Important when comparing data to make sure the data compared was prepared the correct way and done the same each time. |
In general, any measure that can be taken to
For any measure to be valuable in psychological research, it needs to be both valid and reliable (Goodwin, 2008: 128). Research is reliable when more researchers have found the same results, or, within for instance behavioural research, when the same behaviour occurs at several measurements (Goodwin, 2008: 124). There are different types of validity. Firstly, there is construct validity, which measures whether an operationalisation of a construct actually measures what it is supposed to measure. Secondly, criterion validity determines whether a certain phenomenon is related to another phenomenon, and can accurately determine future developments. Lastly, content validity determines whether a test measures all aspects of the construct that is being measured (Goodwin, 2008: 125-126).
Evaluating human services is a task that can be very complex. People can have different interpretations of the same event. Another concern is that people are not always honest. Therefore, human services will gain from effective, high quality evaluations of data collection methods. This requires that the data collection methods supply accurate and dependable information. This paper will define and describe 2 concepts of measurement known as reliability and validity,-provide examples and supporting facts as to how these concepts apply to data collection in human services, and evaluate the importance of the validity and
In the text book, “Theories and Research of Personality” written by Daniel Cervone and Lawrence A. Pervin, the authors talk about the goals to research and they are referring to reliability, validity, and ethical behavior. With reliability, the author is referring to the “extent to which observations can be replicated and whether the measures of the research are dependable or stable” (Cervone, Pervin 43, 2013). Reliability is extremely important to have when conducting research because if the research conducted is not reliable then when trying to get research out to people, other psychologists will not believe what you are trying to get across and in the long term affecting ones career. Also Cervone and Pervin talk about validity which is,
Reliability describes the consistency of a measurement method within a study. (Burns & Grove, 2011) In critiquing the reliability of the Brunner et al. (2012) article, the study was completed at a large urban hospital using three critical care units and two acute care units. The two skin care products were randomly assigned to the participants. The sample size goal in each group was to be 100 participants. Results of the study included that only 64 participants were enrolled. The article written by Brunner et al. (2012) was not reliable for measurement methods. The study is not described in great detail, does not have evidence of accuracy, and has a lack of participants.
The theory of reliability states that it is impossible to calculate the reliability of a study in an exact way. Instead, reliability is estimated and this creates an imperfection in research. There are four major types of reliability. The first is inter-rater or inter-observer reliability. This means the reliability that is used to assess the degree to which the different people who are observing or rating the items being studied give estimates that are consistent regarding the same phenomenon. A good example is the popular example of a glass half empty and one that is half full. This is to mean that people who are in essence similar in every nature may have different ideas or views of the same phenomenon. This kind of reliability is estimated by using a pilot study which is used to establish the expected reliability in the main study(Rosnow & Rosenthal, 2012).
The reliability of an instrument contributes to the level of usability for empirical research (Whiston, 2009). Further, it refers to the replicability andstability of a measurement and whether it will result in the same assessment in the same individuals when repeated (Frankfort-Nachmias & Nachmias, 2008). When determining the reliability of an assessment, a reliability coefficient of at least .80 indicates a trustworthy level of reliability (Trochim, 2006).
Reliability refers to coherence, stability and dependability in test results, generally using internal consistency to express the levels of reliability in the test. The higher reliability indicates the higher level of accordance, stabilization and dependability in test results. Reliability is the precondition of validity (Guba and Lincoln, 1981). The same findings may not generate if the same research is repeated, because many influencing factors may work in the process of research. The process of establishment in reliability research includes: the research rigorously collect and explain data in consistent investigation (internal checks); the process is transparent (sample design, field work, inquiry and rational data). Patton (1987) suggests that the use of triangulation in multiple approaches can increase the reliability in results.
Dependability means do things on time. Dependability means well management and coordination with each operation ensuring other process. are reliable, such as delivering right material or information on time, correct foreseeing and planning the facilities, reorder and workforce. It leads to more effective operation. It effectively arranging the facilities, information, material, workforce, money and time to ensure all of them can be available at any time, saves the time to wait or to look for the other substitutes. Dependability arrangement reduces the chance of repeating input resources or some resources leaving unused increasing the cost of maintain or store fee, or labor cost.
Secondly, dependability. Dependability means reliability, that is, how the company are performing and completing their promised service, quality and accuracy within the given set requirements between the company and the customer. Dependability is just as important as a goof first hand impression, because every customer want to know if their supplier is reliable and fulfill the set requirements with satisfaction. Dependability is just as important as the first hand impression, because every customer wants to know that their supplier of what it may be are reliable and give the service agreed including great quality within the given timeframe without compromising on the quality. Dependability includes three elements, which are consistent order cycles, safe delivery and complete delivery. First of all, we talk about consistent order cycles.