# which of these is not discrete data

These types of data are represented by nominal, ordinal, interval, and ratio values. In theory, a second could be divided into infinite points in time. Examples: # of dimples on a golf ball. Surfaces are continuous data, such as elevation, rainfall, pollution concentration, and water tables. The likelihood of getting these results by chance is very small. Data is generally classified into two categories: descriptive and numerical. The outcome could easily occur by chance. This can be visually depicted as a bar chart. Which of the following consists of discrete data? These data have meaning as a measurement, such as a person’s height, weight, IQ, or blood pressure; or they’re a count, such as the number of stock shares a person owns, how many teeth a dog has, or how many pages you can read of your favorite book before you fall asleep. Example #1. # of people in a stadium. Counted data is discrete. Descriptive data, also called qualitative or categorical data, are represented by words that characterize a set of values while numerical data, known as quantitative data, are denoted by numbers. Test Prep. Data that can only take certain values. The results are very important to the health and well-being of a certain population. Neither is the length of an object, as you use a ruler to measure it. Discrete data is information that can be counted. For example: the number of students in a class (you can't have half a student). Discrete Data is not Continuous Data. The results do not make enough difference to be of use. For example, since you measure your weight on a scale, it's not discrete data. Discrete data and continuous data are the two types of numerical data used in the field of statistics. “Pass/fail” is better for failure analysis: (failure analysis is opposite to the philosophy of Six Sigma. There are two major classes of categorical data, nominal and ordinal. Pages 11; Ratings 93% (122) 114 out of 122 people found this document helpful. This data can be represented as a continuous surface, generally without sharp or abrupt changes. These are also often known as classes or labels in the context of attributes or variables which are to be predicted by a model (popularly known as response variables). This preview shows page 8 - 11 out of 11 pages. Numerical data. These discrete values can be text or numeric in nature (or even unstructured data like images!). Discrete Data. Preventing defects, not trying to figure what went wrong later.) Best at discerning whether or not we have a defective product or service. The likelihood of getting these results by chance is very small. School University of Phoenix; Course Title STATISTICS 145; Type. Continuous vs Discrete Continuous variables such as time, temperature and distance can theoretically be measured at infinitely small points. You can measure time every hour, minute or second. Which one of the following is NOT an example of discrete data A Number of. Discrete features. 50. Which one of the following is not an example of. Uploaded By homewokr3923. Most data fall into one of two groups: numerical or categorical.