Ratio: The ratio of the heights of two women is meaningful. For instance, one woman might be 4/5 the height of another woman.
Height, weight, wavelength of light.
Non-numerical nominal characteristics can be the brands of cars we drive, the names of cities were we live, our race, religion, etc. Numerical nominal characteristics can be area codes, zip codes, numbers on the back of jerseys of basketball players. Numerical, non-nominal data is someone's weight or height.
Yes. (Although it is normally recorded in a discrete form.)
No. Because blood pressure is continuous variable. Like temperature, a person's weight and height, the measured value occurs over a continuous scale.
a continous variable is one that can assume different values at each point, so if you were measuring height it could be 187.1, 187.2.. 187.8, but this can not be used for something such as measuring the amount of people in a family, because there can't be 3.4 people in a family. This is when discrete variable is used, this measures full numbers.
It is ordinal.
Metric data is any reading which is at least at an interval scale, as opposed to non metric data, which can be nominal or ordinal. Weight, height, distance, revenue, cost etc. are interval scales or above. Hence they are metric data. On the other hand, satisfaction ratings, Yes/No responses, Male/Female readings etc., are non metric data.
Nominal-Genda, religion, post, code, ethnic Ordinal-Satisfaction, exam, grade, position in class Interval-IQ, temperature, score, CGPA Ratio-Height, weight, time, age, grant
No. If the variable is continuous, for example, height or mass of something, or time interval, then the set of possible outcomes is infinite.
The average interval was one plane every 45 seconds at the height of the blockade.
Height can be a dependent variable. This is because the adult height of an individual can be markedly affected by environmental and physical variables.
It is a continuous variable.
There are four levels of measurements: 1) Nominal- these are categorized data that are not ordered such as gender, ethnicity, religion, etc. 2) Ordinal-these are categorized data that are ordered such as pain scale, small medium large amounts, first second third place, etc 3) Interval- this is the continuous quantified data with no true zero such as height, or temperature, etc 4) Ratio-this is the continuous data with a true zero such as the body weight, heart rate, etc.
height.
This is the variable which changes as a result of what you change in the experiment. If you change the height from which you drop a ball, you may observe the height to which it bounces. The height of the bounce is the outcome variable.
Ordered Variable is one where you can put the data into order, bt not give it an actual number. The height of a person compared to other's height is an ordered variable.
height is the dependent variable,sun is the independent variable, and height depends on sun