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What scales of measurement are associated with parametric statistics?
Wiki User
∙ 10y ago
nominal and ordinal
Wiki User
∙ 10y ago
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Is the Goal Attainment Scale parametric on nonparametric?
When a person's progress is evaluated using Goal Attainment Scaling their performance is scored on one or more scales with the values +2, +1, 0, -1 and -2, meaning "much better than expected", "better than expected", "expected", "not as well as expected" and "not nearly as well as expected" respectively. If a person were to be evaluated on two scales then their score might be +1 on one scale and -2 on the other, in which case their overall score would be -1--in other words, just the sum of the two scores. You might find many ways of manipulating these total scores in the literature; however, in essence, GAS amounts to the scores on the individual scales plus the total of these scores. There is no single 'Goal Attainment Scale' because the evaluation scales are made up depending on the needs of the person being evaluated. For example, a person with quite limited motor skills might be rated on their ability to climb steps in one scale, on their ability to take a drinking cup from a shelf in another scale, and on their ability to pour milk from a pitcher into a glass in another scale. Notice that the number of scales and the nature of the scales can vary. Because the overall scale value is just a sum it is neither parametric nor nonparametric.
Which of the scale among ratio and interval scale is better in research method topic?
I think Ratio Scale is betterInterval Scale:-Permissible Statistics mean, standard deviation, correlation, regression, analysis of varianceRatio Scale:-Permissible StatisticsAll statistics permitted for interval scales plus the following: geometric mean, harmonic mean, coefficient of variation, logarithmsTo clarify:"Best" is an odd way of looking at it. As the previous answers suggest, ratio data does allow for more advanced statistics, but for the most common forms of analysis, there is little functional difference between the two.The bigger point is that researchers don't necessarily choose the level of data that they are working with. The nature of whatever they are studying determines it, and you can get into some pretty murky water when you try to force a ratio measurement in a study where it isn't really appropriate.
What is the primary difference between rating scales and ranking scales?
ranking deals with multi choice and rating is fixed with attributes
Difference between interval scale and ratio scale?
an ratio scale is where both measurements are in the same unit of measurement and an interval scale is where they are not. i dont know if this helps at all but we are learning about it in maths at the moment and that is the easiest way for me to understand it Beside the features of interval scales, ratio scale carries zero point measurements. Means that the zero value is considered when we do the measurement in ratio scales. Say that it is not only differ between 1 to 10, but there is also different to compare two intervals between 1 to 10, and 100,001 to 100,010 when we measure them (intervals) starting from zero point scales. * * * * * Unfortunately, the first paragraph above is nonsense. An interval scale is one in which the difference between two points can be quantified numerically. However, the zero is arbitrary. The Celsius and scale is an example. The difference between 1 deg C and 3 deg C is twice the difference between 7 deg and 8 deg. But 3 deg C is not 3 times as hot/cold as 1 deg C. A ratio scale is an interval scale with the added requirement of a non-arbitrary zero point such that the value of 3 is three times the value of 1. The Kelvin scale meets those requirements. Scales in common use, that are not interval are the Richter scale (earthquakes) or Beaufort (wind speeds) where the points on the scale are indicators of outcomes.
What is the colleration?
Fish Scales or the water displaced by collerational pie to mc power of 5
Which of these measurement scales has a rank order associated with its use?
ordinal
What are examples of spring scales?
measurement
What is the definition of deceptive statistics?
Lies or damned lies! These would be statistics which are faulty or presented in a misleading way (deliberately or accidentally). Such statistics could arise in a number of ways:the experimental model was flawed,there were errors in measurement or recording,the sample was biased,correlation was interpreted as causation,poor graph design - scales, pictograms using improper dimensions,
What is the most accurate form of measurement?
using scales and instruments
What measurement scales is related to naming and classifying?
The nominal scale.
What are scales?
scales are 3 things1. Measurement Item2. Little Shiny things on an animal3.It is like a coat of armor for a fish
How many type of variable?
This question could be answered in a variety of ways. In statistics for the biological sciences we use scales of measurement for variable types. In this case there are 4 types of variables: nominal (aka categorical), ordinal, interval (aka scale), and ratio.
How does the moment magnitude and Richter scales of earthquake measurement are similar and how they are different?
the answer is qotes
What are two types of measurements?
Types of measurement scales include industrial scales, bathroom scales, and kitchen scales. Each is designed to weight different size objects at varying degrees of accuracy.
What type of chart displays a column and line chart using different scales of measurement?
Combination
What is the unit of measurement of hotness and coldness?
The measurement used for hotness and coldness are degrees. There are two scales used Fahrenheit (F) and Celsius (C) with a little ball to the right of the measurement.
What is nominal level of measurement?
Nominal level of measurement is defined as the level of measurement that classifies variables by assigning names or categories that are mutually exclusive and exhaustive. It was often called qualitative scales, and measurements made on qualitative scales were called qualitative data. Examples are gender, nationality, ethnicity, language, genre, style, biological species, and form.
