Question

There are four scales of measurement: nominal, ordinal, interval, and ratio. Explain how aggression might be assessed using each of these measurement scales

Answer 1

Answer:

Variables are dimensions using a device or computer. The variable measured extremely affects the type of analytical techniques that can be used on the data, and what decisions can be drawn from the data. Therefore four scales of capacity, nominal, ordinal, interval, and ratio. The amount of information is limited in nominal scale data, while the most amount of information can be obtained from ratio scale data.

Nominal: Nominal measures consign numbers as labels to classify objects of objects. The assigned numbers bring no more meaning except as identifiers. For example, the use of aggressive, normal, and passive drivers is a nominal measure variable. Point that the order has no sense here, and the difference between identifiers is meaningless.

In practice, it is to assign numbers instead of letters to represent nominal scale variables, but the numbers might not be treated as ordinal, interval, or ratio measures variables.

For example, one cannot say that Males are very aggressive than Females, or vice-versa.

Ordinal: Ordinal measures build upon nominal scales by assigning numbers to objects to reflect a rank ordering on an attribute in question.

We can measure aggression by relating this below example.

For example, assigning ID codes 1, 2 and 3 to represent a Individual’s response to a question by using rate: 1 = use; 2 = use sometimes; 3 = never use. However, the order matters in these variables except nominal scale variables, the variance between replies are not reliable across the scale or across individuals who respond to the question.

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Interval: This scale constructs upon ordinal scale variables. In this, numbers are assigned to objects such that the differences between the numbers can be meaningfully inferred.

If I relate the aggression as an example in the form of Temperature, Celsius, Fahrenheit signifies an interval scale variable, because the difference between measurements is the same anywhere along the scale, and is consistent across measurements. Proportions of interval scale variables have partial meaning because there is not an utter zero for interval scale variables. The temperature scale in Kelvin, in disparity, is a ratio scale variable because it’s zero value is completely zero, for example, nothing can be measured at a lower temperature than 0 degrees Kelvin.

Ratio: This scale has all the qualities of interval scale variables and one more attribute: ratio scales include a total “zero” point. For example, you can measure a child's aggressive behavior by counting the number of times that the child inflicts physical harm on another person during a month observation period.