You'll see that there are very few simple rules that will make the decision for you -- you have to use your judgment to balance the advantages and disadvantages of different survey types.
X X You will notice in the above table that only the ratio scale meets the criteria for all four properties of scales of measurement. Interval and Ratio data are sometimes referred to as parametric and Nominal and Ordinal data are referred to as nonparametric.
Parametric means that it meets certain requirements with respect to parameters of the population for example, the data will be normal--the distribution parallels the normal or bell curve.
In addition, it means that numbers can be added, subtracted, multiplied, and divided. Parametric data are analyzed using statistical techniques identified as Parametric Statistics. As a rule, there are more statistical technique options for the analysis of parametric data and parametric statistics are considered more powerful than nonparametric statistics.
Nonparametric data are lacking those same parameters and cannot be added, subtracted, multiplied, and divided. For example, it does not make sense to add Social Security numbers to get a third person.
Nonparametric data are analyzed by using Nonparametric Statistics. As a rule, ordinal data is considered nonparametric and cannot be added, etc.
Again, it does not make sense to add together first and second place in a race--one does not get third place. However, many assessment devices and tests e.
For example, the "average" amount of pain that a person reports on a Likert-type scale over the course of a day would be computed by adding the reported pain levels taken over the course of the day and dividing by the number of times the question was answered.
Theoretically, as this represents ordinal data, this computation should not be done. As stated above, many measures e. IQ scores may be computed for a group of individuals. They will represent differences between individuals and the direction of those differences but they lack the property of indicating the amount of the differences.
Psychologists have no way of truly measuring and quantifying intelligence. An individual with an IQ of 70 does not have exactly half of the intelligence of an individual with an IQ of Indeed, even if two individuals both score a on an IQ test, they may not really have identical levels of intelligence across all abilities.
Therefore, IQ scales should theoretically be treated as ordinal data. In both of the above illustrations, the statement is made that they should be theoretically treated as ordinal data. In practice, however, they are usually treated as if they represent parametric interval or ratio data.
This opens up the possibility for use of parametric statistical techniques with these data and the benefits associated with the use of techniques. Hopefully, the discussion above has helped you to understand a little better what the terms measurement and statistics mean.
However, you may still be wondering "Why do I need to learn statistics? The first reason is to be able to effectively conduct research. Without the use of statistics it would be very difficult to make decisions based on data collected from a research project. For example, in the study cited above, is the difference in recorded absenteeism between psychiatric and obstetrics nurses large enough to conclude that there is meaningful difference in absenteeism between the two units?
There are two possibilities: The first possibility is that the difference between the two groups is a result of chance factors. In reality, the two jobs have approximately the same amount of absenteeism. The second possibility is that there is a real difference between the two units with the psychiatric unit demonstrating that these nurses miss more work.
Without statistics we have no way of making an educated decision between the two possibilities. Statistics, however, provides us with a tool with which to make an educated decision.
We will be able to decide which of the two possibilities is more likely to be true as we base our decision on our knowledge of probability and inferential statistics. A second point about research should be made.
It is extremely important for a researcher to know what statistics they want to use before they collect their data. Otherwise data might be collected that is not interpretable. Unfortunately, when this happens it results in a loss of data, time, and money.
Now many a student may by saying to themselves: Certainly, if you decide to continue your education and work on a masters or doctoral degree, involvement in research will result from that decision. Secondly, more and more work places are conducting internal research or are part of broader research studies.
Thus, you may find yourself assigned to one of these studies.What are some critical decisions involved in selecting an appropriate measurement scale? How do these decisions influence the research design? First part is Please answer the four questions below leaving the questions on top and answering below, words each.
1. How does technological advancement affect the ability to collect data? Provide . Research Methods is a text by Dr. Christopher L. Heffner that focuses on the basics of research design and the critical analysis of professional research in the social sciences from developing a theory, selecting subjects, and testing subjects to performing statistical analysis and writing the research report.
Each scale of measurement has certain properties which in turn determines the appropriateness for use of certain statistical analyses. The four scales of measurement are nominal, ordinal, interval, and ratio. For portfolio risk assessment, investment decision, or analysis of alternatives tasks, using categories of risk area scales may be the most appropriate way to ensure each alternative or .
What are some critical decisions What are some critical decisions involved in selecting an appropriate measurement scale and how do these decisions influence the research design?
Submitted: days and 14 hours ago. A measurement approach that he might consider for this is the: Strategic Profit Model You are an upper level manager in a firm and are concerned that corporate objectives are not effectively disseminated throughout the organization and that line level managers do not take them account in making their decisions.