what is the difference between scale and ordinal in spss?
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In summary, nominal variables are used to “name,” or label a series of values. Ordinal scales provide good information about the order of choices, such as in a customer satisfaction survey. Interval scales give us the order of values + the ability to quantify the difference between each one.
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Rating scales do not produce qualitative data, irrespective of what the end-point labels may be. Data from Likert scales and continuous (e.g. 1-10) rating scales are quantitative. These scales assume equal intervals between points.
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Scale. A variable can be treated as scale when its values represent ordered categories with a meaningful metric, so that distance comparisons between values are appropriate. Examples of scale variables include age in years, and income in thousands of Rupees, or score of a student in GRE exam.
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There seems to be some confusion over variable being measured (age is ratio, period) and the way in which it is measured (always a discrete variable, so the measurement by ranges of ages is ordinal, but age is ratio).
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Data at the nominal level of measurement are qualitative. No mathematical computations can be carried out. Data at the ordinal level of measurement are quantitative or qualitative. ... Data at the interval level of measurement are quantitative.
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Both depend on how their high school calculates GPA. Some high schools report GPA on a 5.0 scale instead of a 4.0 scale. So, a 4.5 GPA on a 5.0 scale is the equivalent of a 3.5 GPA on a 4.0 scale. Most high schools use a 4.0 scale, however, because most colleges use a 4.0 scale.
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Nominal scale is a naming scale, where variables are simply “named” or labeled, with no specific order. ... Ratio scale bears all the characteristics of an interval scale, in addition to that, it can also accommodate the value of “zero” on any of its variables.
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Assuming you've defined them in order of severity, you can compare the ordinals of each value. The ordinal is its position in its enum declaration, where the initial constant is assigned an ordinal of zero. You get the ordinal by calling the ordinal() method of the value. Java enum has already build in compareTo(..)
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A scale is virtually used for measurements along a straight line. A ruler need not be used for this purpose. The use of scale is simple in purpose whereas that of a ruler is complex in purpose. A ruler with straight edge is used with a little bit of an extra advantage than a scale.
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Ordinal data can also be quantitative or numeric. When asked to rate your level of financial happiness, for example, the values are numeric. However, numerical operations (addition, subtraction, multiplication etc.)
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There is huge difference between SPSS and Excel. Excel is spreadsheet software, SPSS is statistical analysis software. In Excel you can perform some Statistical analysis but SPSS is more powerful. ... SPSS alow you to perform complex analytics such as factor analysis, logistic regression, cluster analysis etc.
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Nominal scale is a naming scale, where variables are simply “named” or labeled, with no specific order. Ordinal scale has all its variables in a specific order, beyond just naming them. Interval scale offers labels, order, as well as, a specific interval between each of its variable options.
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Indexes and Scales An index really just means that it is a measurement that is constructed by summing up other, simpler, measurements. A scale is an index that in some sense only measures one thing. For example, a final exam in a given course could be thought of as a scale: it measures competence in a single subject.
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A nominal variable has no intrinsic ordering to its categories. For example, gender is a categorical variable having two categories (male and female) with no intrinsic ordering to the categories. An ordinal variable has a clear ordering.
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Categorical variables can be sub-classified as nominal or ordinal with ordinal variables have a natural ordering, whereas nominal variables do not. Gender, Diabetes and Race/Ethnicity were nominal categorical variables, they have no natural order and individuals can only be put into categories for these variables.
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Nominal, ordinal, or numerical variables? ... Nominal data is classified without a natural order or rank, whereas ordinal data has a predetermined or natural order. On the other hand, numerical or quantitative data will always be a number that can be measured.
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In research activities a YES/NO scale is nominal. It has no order and there is no distance between YES and NO. There are also highly sophisticated modelling techniques available for nominal data. An ordinal scale is next up the list in terms of power of measurement.