Statistics Assessment : Social Research Skills

The questions in this instrument are weighted a numerical value of zero to three, with three being the highest score on each question.

1. A fast-food restaurant asks customers to evaluate the drive-thru service as good, average, or poor. What level of data measurement is this classification?

b. Dependent Variable: the variable that I am measuring (it depends on the independent variable)

2. Data from Likert scales and continuous (e.g. 1-10) rating scales are quantitative. Allows you to measure their feeling on a scale of 1

Measurement that shows the order or rank of items. An example of ordinal could be ranking places in a contest, or test scores.

(1) A study of the number of cars sold looked at the number of cars sold at 500

1. The researchers analyzed the data they collected as though it were at what level of measurement?- The correct answer is Interval/ratio.

b. Ordinal: This is a measurement that represent the order of a particular stat. A good example of this would the placement in a contest, 1st, 2nd, and 3rd.

6) This is an experiment because it is in a controlled environment where the variables and the situation are manipulated. The dependant variable is the preference of the participants. The

Above is an example or both primary and secondary data which is all quantitative being based on proven facts and subject to continual improvement.

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?

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.

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

The following are examples of nominal, ordinal, interval and ratio levels variables with explanations of why. Examples of nominal level data would include different medications classifications such as ACE or ARB inhibitors, hypoglycemic agents, neuroleptics, antibiotics, etc. They are considered nominal because they cannot be placed in an order different categories, there is no measureable distance between them and there is no relationship in list order (Marateb, et al., 2014). An example of ordinal level data would include Likert-type scale variables, pain level scales, or social status. They are considered ordinal because they indicate a direction as well as provide nominal information (Marateb, et al., 2014). Interval level data examples

This phrase is applied to social sciences to point to the location, size or scale of a research target. It is unique from the term ‘unit of observation” as the former relates to an integrated set of relationships while the latter is about the distinct unit from which data will be gathered. The levels of analysis are not mutually exclusive but an in critical discuss analysis research generally falls under micro level and the macro level of analysis.