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Data Analysis - Essay Example
Pages 20 (5020 words)
Gender is a discrete variable which can take on either male or female values. It has a non-parametric nominal level of measurement because its value represents a category of objects where there is no measured difference between its values (Black 2006, p.8).
Blood pressure is a discrete variable where its value can only take on certain values. Its level of measurement is parametric interval because its values can be ordered and the distance between different values has a meaning (Black 2006, p.9).
The height variable is a continuous variable where its value can be set to any value. It has an interval level of measurement as its different values are ordered and the difference between different values has a meaning (Black 2006, p.9).
Temperature is a continuous variable because it can be equal to any real value. It has a parametric interval level of measurement since its values can be ordered and difference between different variable has a meaning. The zero value of temperature does not mean an absolute null value.
The Satisfaction rating variable is a discrete variable since its value can only be set to specific values. It has a non-parametric ordinal level of data because its values are categories which can be ordered (Black 2006, p.8).
Employment status is a discrete variable since it can be set to only one of two possible values. It has a non-parametric nominal level of data since its values are categories which can not be ordered (Black 2006, p.8).
Examples of ordinal data that occur in categories but can be ordered are: heart murmurs grades I (heard only with special effort) to VI (audible with the stethoscope off the chest), the risk of birth defects from drugs ...
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