1. Thus, Z is a continuous variable, but if we add an additional restriction as “a student’s height to the nearest centimeter”, then the variable Z will be discrete since it can take only a finite number of values. Frequency Distribution of a Discrete Variable Since, a discrete variable can take some or discrete values within its range of variation, it will be natural to take a separate class for each distinct value of the discrete variable as shown in the following example relating to the daily number of car accidents during 30 days of a month. A continuous variable is any variable that can be any value in a certain range. Ordinary qualitative variables are known as semi-quantitative variables. variable, or a continuous quantitative variable. Whenever you are asked to discern discrete and continuous variables, think about their most distinguishing features. Quantitative variables are measured and expressed numerically, have numeric meaning, and can be used in calculations. A continuous variable is a specific kind a quantitative variable used in statistics to describe data that is measurable in some way. ; Most often these variables indeed represent some kind of count such as the number of prescriptions an individual takes daily.. Continuous variables are continuous on a scale, the values between the figures have meaning and the data can be fragmented into parts. The continuous variables can take any value between two numbers. Discrete variables are specific points on a scale. By now you already know what entails to a statistical variable and how to differentiate continuous vs discrete variables. An example of this type of variables can be the result of a sport competition (first, second or third place). Conclusion of the Main Difference Between Discrete vs Continuous Variables. Quantitative variables are measured and expressed numerically, have numeric meaning, and can be used in calculations. Although they allude to attributes or qualities that lack a numerical value, they are classified within a scale of value. For example, between 50 and 72 inches, there are literally millions of possible heights: 52.04762 inches, 69.948376 inches and etc. Some examples of continuous variables are measuring people's weight within a certain range, measuring the amount of gas put into a gas tank or measuring the height of people. In a dataset, we can distinguish two types of variables: categorical and continuous. For example, between 50 and 72 inches, there are literally millions of possible heights: 52.04762 inches, 69.948376 inches and etc. My point is that "continuous" should not be used for discrete quantitative variables. Percentage mark on an exam, length of a frogs jump are continuous. For instance, we could perform a regression analysis to see if the weight of Jujube boxes (continuous data) is correlated with the number of Jujubes inside (discrete data). From this, it can be seen that normally a continuous variable is defined as a measurement. In a nutshell, discrete variables are points plotted on a chart and a continuous variable can be plotted as a line. A quantitative variable where there is a continuous (no infinite number) of attributes. Learn about the Math Variables that can be measured in terms of numbers, such as height, mass, and shoe size, are called quantitative variables. Quantitative variables represent amounts of things (e.g. I record all the tricks here to determine a qualitative (categorical), quantitative, nominal, ordinal, discrete, and continuous variable.