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