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Attributes are closely related to variables. A variable is a logical set of attributes. [1] Variables can "vary" – for example, be high or low. [1] How high, or how low, is determined by the value of the attribute (and in fact, an attribute could be just the word "low" or "high"). [1] (For example see: Binary option)
For the variables under examination, analysts typically obtain descriptive statistics for them, such as the mean (average), median, and standard deviation. [61] They may also analyze the distribution of the key variables to see how the individual values cluster around the mean. [62] An illustration of the MECE principle used for data analysis.
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. Data collection is a research component in all study fields, including physical and social sciences, humanities, [2] and business ...
Examples of measured variables could be the physical height, weight, and pulse rate of a human being. Usually, researchers would have a large number of measured variables, which are assumed to be related to a smaller number of "unobserved" factors. Researchers must carefully consider the number of measured variables to include in the analysis. [2]
Data are commonly used in scientific research, economics, and virtually every other form of human organizational activity. Examples of data sets include price indices (such as the consumer price index), unemployment rates, literacy rates, and census data. In this context, data represent the raw facts and figures from which useful information ...
The same is true for intervening variables (a variable in between the supposed cause (X) and the effect (Y)), and anteceding variables (a variable prior to the supposed cause (X) that is the true cause). When a third variable is involved and has not been controlled for, the relation is said to be a zero order relationship. In most practical ...
The variables made to remain constant during an experiment are referred to as control variables. For example, if an outdoor experiment were to be conducted to compare how different wing designs of a paper airplane (the independent variable) affect how far it can fly (the dependent variable), one would want to ensure that the experiment is ...
Such distinctions can often be loosely correlated with data type in computer science, in that dichotomous categorical variables may be represented with the Boolean data type, polytomous categorical variables with arbitrarily assigned integers in the integral data type, and continuous variables with the real data type involving floating point ...