are yes and no answers nominal data?
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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.
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Qualitative data is of two types, namely; nominal data and ordinal data. Qualitative data sometimes takes up numeric values but doesn't have numeric properties. This is a common case in ordinal data. Ordinal data have a scale and order to it.
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The rules for doing that are defined by the specification: Basically, if the value is undefined , null , "" , 0 , or NaN , it coerces to false ; otherwise, it coerces to true . So ! undefined is true because undefined implicitly converts to false , and then ! negates it.
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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.
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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. They can be arranged in order (ranked), but differences between entries are not meaningful.
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When you go on the "carousel" thing it will ask No, maybe, or Yes. Eah time you click on the 'maybe' or 'yes' icon you are awarded a point and thy may be accumulated, no limit. Has nothing to do wif you may or may not contact them. Contact comes with the paid subscription.
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Discrete data have finite values, or buckets. You can count them. Continuous data technically have an infinite number of steps, which form a continuum.
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Answering Tag Questions. When you answer a tag questions, often you can just say 'yes' or 'no'. To give the full answer, you use the same auxiliary or modal verb that was used in the question.
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Negative Questions. A negative question is one that is worded in such a way as to require a “no” response for an affirmative answer and a “yes” response for a negative answer. In other words, negative questions switch the “yes/no” response order of regular, or positive, questions to a less intuitive “no/yes” order.
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In economics, the nominal values of something are its money values in different years. ... But nominal values do not specify how much of the difference is from changes in the price level. Real values remove this ambiguity. Real values convert the nominal values as if prices were constant in each year of the series.
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Age can be both nominal and ordinal data depending on the question types. I.e "How old are you" is a used to collect nominal data while "Are you the first born or What position are you in your family" is used to collect ordinal data. Age becomes ordinal data when there's some sort of order to it.
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Question: Determine Whether The Variable Is Qualitative Or Quantitative. Street Name Of Address Is The Variable Qualitative Or Quantitative? A. The Variable Is Quantitative Because It Is An Attribute Characteristic B.
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Unlike nominal- and ordinal-level data, which are qualitative in nature, interval- and ratio-level data are quantitative. Examples of interval level data include temperature and year. ... The scales differ in that the zero point is arbitrary on interval scales, but not on ratio scales.
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Yes–no question. In linguistics, a yes–no question, formally known as a polar question or a general question is a question whose expected answer is either "yes" or "no". Formally, they present an exclusive disjunction, a pair of alternatives of which only one is acceptable.
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"Answer" is strongly countable: it is very rare (perhaps impossible) to find 'answer' as an uncountable noun.
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Surveys (questionnaires) can often contain both quantitative and qualitative questions. The quantitative questions might take the form of yes/no, or rating scale (1 to 5), whereas the qualitative questions would present a box where people can write in their own words.
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To recap, nominal scales have labels, the value and order of options don't matter. Ordinal scales have labels, the order matters, but the value doesn't. Interval scales have labels, the order matters, and the values matter but there's no zero.