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

which of these is not discrete data

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which of these is not discrete data 2020