Types of Data- TJHSST Larson IBET

TYPES OF DATA

QUANTITATIVE DATA
	Quantitative data are represented by a number and a unit of measurement, such as the Metric system of measurement or the Arabic system of numbers. Examples of quantitative variables are the height of a person in meters, the mass of rabbits in kilograms, and the number of seeds that germinated. Quantitative variables may be continuous or discrete. Continuous quantitative data are collected using standard measurement scales that are divisible into partial units, for example, distance in kilometers and volume in liters. Discrete quantitative data are collected using standard scales in which only whole integers are used, for example, the number of wolves born in a given year or the number of people that can touch their toes. In this chapter, the same statistical techniques will be used with continuous and discrete quantitative data. As shown in the examples below [actually not; can't put graphics in here], and explained later, [actually not, don't have the pages] graphic presentations differ.
	Quantitative data can be further subdivided based on the zero point of the measuring scale. When quantitative data are collected using a standard scale with equal divisible intervals and an absolute zero, it is called ration data. Examples include the temperature of a gas on the Kelvin scale, the velocity of an object in m/sec, and the distance from a point in meters. If the scale does not have an absolute zero, the data are called interval data. A common example is the temperature of a substance on the Celsius scale. On this scale, changes in water temperature from 90 to 95 degrees and from 60 to 65 degrees represent the same amount of increase in heat energy or kinetic energy of the molecules. There is no absolute zero, however, because water molecules are still moving at 0°C. In fact, a substance must reach -273°C (0° Kelvin) before molecular motion ceases. In this chapter, the same statistical and graphical techniques are used with ratio and interval data. Mathematically, however, ratio data can be used in a ratio and proportion, whereas interval data cannot. This is why you convert the temperature of gases in degrees Celsius to Kelvin before solving problems with Charles Law or the Ideal Gas Law.

QUALITATIVE DATA
	Qualitative data are classified into categories. The categories may be discrete categories represented by a word or "number" label or measurements made with a nonstandard scale with unequal intervals. Examples include the gender of an organism and the color of an individual's eyes. The discrete categories are defined by the experimenter and may be based on a literature review or reflect a synthesis of many observations made during experimentation.
	`Subdivisions of qualitative data are based on the ability to rank order the categories. Nominal data exists when objects have been named or placed into discrete categories that cannot be rank ordered, for example, gender (male/female) and the color of hair(red, black, brown). Ordinal data exists when objects are placed into categories that can be rank ordered. For example, the activity of an animal could be rated on a scale of 1 to 5, with 5 representing a very active animal. Another example of ordinal data is Moh's Hardness Scale for Minerals. Different statistical techniques and graphic presentations are used for nominal and ordinal data.