Time is ratio data because it has a true, meaningful data. You can say that at time 20 seconds, it is twice the amount of time than 10 seconds.
Interval data doesn't have a true zero e.g. degrees celcius. Although you can say 60 degrees is hotter than 30 degrees you can't say that it is twice as hot.
It is a HISTOGRAM.
No.
A variable measured at the interval or ratio level can have more than one arithmetic mean.
He discovered the ratio of a perfect octave is 2:1.
He discovered the ratio interval of a perfect octave is 2:1.
interval
Yes.
Yes, they do exist.
It is a HISTOGRAM.
Age is none of the items listed. Age is ratio data.
No; since you refer to a math score (and not a math grade), it is ratio data.
Data comes in various sizes and shapes. Two of them are Interval and Ratio. Interval is a measurement where the difference between two values is meaningful and follows a linear scale. For example: in physics, temperature 0.0 on either F or C does not mean 'no temperature'; in biology, a pH of 0.0 does not mean 'no acidity'. Interval data is continuous data where differences are interpretable, ordered, and constant scale, but there is no 'natural' zero. Ratio is the relation in degree or number between two similar things or a relationship between two quantities, ordered, constant scale, with natural zero. Ratio data is interpretable. Ratio data has a natural zero. A good example is birth weight in kg. The distinctions between interval and ratio data are slight. Certain specialized statistics, such as a geometric mean and a coefficient of variation can only be applied to ratio data.
Yes, a set of ordinal, interval, or ratio level data can have one mode, which is the value that appears most frequently in the dataset. In ordinal data, the mode represents the most common category, while in interval or ratio data, it reflects the most frequently occurring numerical value. However, it is also possible for such datasets to have no mode or multiple modes, depending on the distribution of the values.
Ratio and interval data are both types of quantitative data in statistics. Interval data has meaningful differences between values, but lacks a true zero point, meaning you cannot make meaningful statements about ratios (e.g., temperature in Celsius). In contrast, ratio data has both meaningful differences and a true zero point, allowing for both differences and ratios to be interpreted (e.g., weight or height). This distinction is important for determining the appropriate statistical analyses to use.
Interval-Ratio can use all three measures, but the most appropriate should be mean unless there is high skew, then median should be used.
Telephone numbers are actually nominal data.
Four types of intermittent schedules of reinforcement are fixed ratio, variable ratio, fixed interval, and variable interval. Fixed ratio schedules provide reinforcement after a set number of responses, while variable ratio schedules provide reinforcement after a varying number of responses. Fixed interval schedules provide reinforcement after a set time interval, while variable interval schedules provide reinforcement after a varying time interval.