what is the difference between continuous and attribute data?
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Attribute data are usually collected when standard measurements are difficult to obtain. Continuous variables can have an infinite number of values, but attribute variables can only be classified into specified categories. The advantage of continuous measurements is that they usually give much more information.
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['Discrete variables represent counts (e.g. the number of objects in a collection).', 'Continuous variables represent measurable amounts (e.g. water volume or weight).']
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Discrete data is information that can only take certain values. ... This type of data is often represented using tally charts, bar charts or pie charts. Continuous data is data that can take any value. Height, weight, temperature and length are all examples of continuous data.
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The difference is subtle. Attributes are refering to additional information of an object. Properties are describing the characteristics of an object. Most people use these two words as synonyms.
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What is the difference between a categorical and continuous variable? Categorical are assigned to discrete categories; continuous can take any value in a range. ... Explanatory is the factor that varies in an experiment; response is measured as the explanatory variable varies.
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Differences Between Class and Instance Attributes The difference is that class attributes is shared by all instances. When you change the value of a class attribute, it will affect all instances that share the same exact value. The attribute of an instance on the other hand is unique to that instance.
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Answer: Continuous if looking for exact age, discrete if going by number of years. If a data set is continuous, then the associated random variable could take on any value within the range.
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The difference between interval and ratio data is simple. Ratio data has a defined zero point. Income, height, weight, annual sales, market share, product defect rates, time to repurchase, unemployment rate, and crime rate are examples of ratio data.
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We know an attribute is a quality or characteristic of a person, place, or thing. It's an identifying label that alludes to something inherent about them, like charm or cruelty. ... Meanwhile, a trait is an ingrained characteristic or habit that is difficult to learn or unlearn, like shyness or confidence.
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While both provide context for business transactions, reference data is concerned with classification and categorisation, while master data is concerned with business entities. ... For example, adding a new customer or sales product is part of the standard business process.
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A discrete variable has a complete range of values. ... A continuous variable is uncountable while a discrete variable has countable values. The data set for a discrete variable is finite meaning it has an end value while a continuous variable can take up an infinite value which implies that it can have endless values.
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Simple attribute − Simple attributes are atomic values, which cannot be divided further. ... Single-value attribute − Single-value attributes contain single value. For example − Social_Security_Number. Multi-value attribute − Multi-value attributes may contain more than one values.
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Discrete data can be numeric -- like numbers of apples -- but it can also be categorical -- like red or blue, or male or female, or good or bad. Continuous data are not restricted to defined separate values, but can occupy any value over a continuous range.
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Attribute data is defined as information used to create control charts. ... Variable data is defined as information and figures used to build control charts. Variable data can be used to create average (X-bar) charts, range charts, and sample standard deviation charts or "S-charts."
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Terms in this set (21) What is the primary difference between an entity and an attribute? An entity (also known as a table) stores information about people, places, or events, whereas an attribute is a column or specific field of the data elements associated with an entity.
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What is the primary difference between an entity and an attribute? A) An entity is information about a column or specific field of the data elements associated with an entity, whereas column is information about people places and events. ... An attribute is a field that uniquely identifies.
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Ordinal data are most concerned about the order and ranking while interval data are concerned about the differences of value within two consecutive values. 2. Ordinal data place an emphasis on the position on a scale while interval data are on the value differences of two values in a scale.