Nominal data is the most basic level of measurement. It is also known as categorical. The numbers do not imply an order. Basically nominal data is used for frequency and the only number property of the nominal scale of measurement is identity. An everyday example of the use of nominal data would be classifying people according to gender is a common application of the nominal scale. When you first meet someone, an observation is generally made on the specific gender of the person you are meeting for the first time.
Identify and define the four scales of “Natural Measurement”. How are they interrelated? How do they relate to inferential (causal) statistics? Is there a preferred level of measurement? Why or why not?
Determine which of the four levels of measurement is most appropriate and explain your answer.
Typically there are four different levels of measurements for variables. These are nominal, ordinal, interval and ratio. Nominal measurement is a numerical value. An example in the High School Longitudinal Study database used are the year’s math teacher has taught high school math. Ordinal measurement are the features that can be categorized. An example of this would be if you’re ranked the highest education of the parents. An ranking example is reflected below chart
1. The researchers analyzed the data they collected as though it were at what level of measurement?- The correct answer is Interval/ratio.
C. The researchers analyzed the data as though it were at the interval/ratio level since they calculated means (the measure of central tendency that is appropriate only for interval/ratio level data) and standard deviations (the measure of dispersion for interval/ratio data) to describe their study variables.
Without designed or determined variables, a research cannot be conducted. As denoted in Meyers et al. (2013) “As a rather conceptual but important characterization, a variable is an obstruction or construct that can take on different values.” The values of variables could be numbers expressing quantitative meaning (Meyers et al., 2012). “Quantitative” relates to numerical values, it may also justify the weight or variability of any population; it also can be anything represented by numerical values. Some values may be represented by names of people or animals. Such values are used to determine “qualitative” or categorical differences between cases (Meyers et al., 2013). In terms of measurement, I have apprehended that there are five scales of measurements. There are as follows: Ordinal, Nominal, Summative response, Interval, and Ratio scales (GCU, 2012). From the PSYC 845, I have also recall of learning about the ANOVA research design. As noted by Santayana (2011): “Measurement is at the core of doing
Measurement is a significant area in the curriculum, as it can “make or break a child’s confidence in mathematics” (Kefaloukos & Bobis, 2011, p. 19). Therefore teachers play a crucial role in teaching this area of maths. Firstly, it is important to consider what skills children have with regard to measurement when they start school. This guides teachers with an appropriate level to begin. Secondly, teachers need to know some engaging ways to teach measurement. Teachers also need to know how to adjust their teaching when necessary to cater for a varied range of abilities.