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.
Height, weight, wavelength of light.
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.
Yes, the height from which the ball is dropped is the independent variable in this scenario. It is the variable that is intentionally changed or manipulated to observe its effect on the height of the ball's bounce, which is the dependent variable.
The average interval was one plane every 45 seconds at the height of the blockade.
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 can be a dependent variable. This is because the adult height of an individual can be markedly affected by environmental and physical variables.
The height from which the ball is dropped is the independent variable, as it is what is being manipulated. The height of the ball's bounce is the dependent variable, as it is what is being measured and is affected by the height from which the ball is dropped.
It is a continuous variable.
height.
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.