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</html>";s:4:"text";s:13503:"Continuous: Height, weight, annual income. For example, take an age. Continuous variables would take forever to count. Data Data Index. Solution for Which is an example of continuous data? Examples of continuous data include time. The first graph shows discrete data. Weight, height, temperature, etc. Discrete data (like number of … Continuous data represent measurements; their possible values cannot be counted and can only be described using intervals on the real number line. Quantitative data is data where the values can change continuously, and you cannot count the number of different values. Continuous data is the data that can be measured on a scale. Ocean currents are continuous data because they can be measured at infinite levels of detail at infinite points in time.The test results of 300 students who write a multiple choice exam with 65 points is discrete because both students and points are counted with no measurements possible inbetween. If you consider a value line, the values can be anywhere on the line. For statistical purposes this kind of data is often gathered in classes (example height in 5 cm classes). Examples of continuous data. For example, taking the average temperatures for each month during a year is an example of continuous data. Some examples of continuous data include: The weight of newborn babies; The daily wind speed; The temperature of a freezer; When you think of experiments or studies involving constant measurements, these likely involve continuous variables to some degree. (Revolutionary definition, I … Examples of continuous data: The amount of time required to complete a project. Basically, anything you can measure or count is quantitative. If you’ve got a number like “2.86290” anywhere on a spreadsheet, this is not a number you could have easily arrived at … It can take any numeric value, within a finite or infinite range of possible value. In fact, we would get to forever and never finish counting them. Remember that you know this because the data points are not joined. Examples include time, height and weight. Examples include weight, price, profits, counts, etc. 1.Shirt Size 2.Class Size 3.Amount of water consumed in a day 4.Number of taxi cabs in a fleet You might pump 8.40 gallons, or 8.41, or 8.414863 gallons, or any … Quantitative data is data where the values can change continuously, and you cannot count the number of different values. Examples include weight, price, profits, counts, etc. Discrete: Number of children, number of students in a class. The second type of continuous surface data includes phenomena that progressively vary as they move across a surface from a source. The continuous data can be broken down into decimal and fractions ,so it can be subdivided into smaller parts according to the measurement precision. Continuous data (like height) can (in theory) be measured to any degree of accuracy. are examples of measurement that would make up a continuous data set. Basically, anything you can measure or count is quantitative. Continuous Data. Solution for Which is an example of continuous data? Examples of progressively varying continuous surface data are fluid and air movement. Note: “range” refers to the difference between highest & lowest observation. The amount of time it takes to sell shoes. We can’t count “age”. One hour can be divided into two groups of thirty minutes, minutes can be divided into seconds and seconds can continue to be divided on down the line. For example, the exact amount of gas purchased at the pump for cars with 20-gallon tanks would be continuous data from 0 gallons to 20 gallons, represented by the interval [0, 20], inclusive. 1.Shirt Size 2.Class Size 3.Amount of water consumed in a day 4.Number of taxi cabs in a fleet Continuous Data can take any value (within a range) Examples: A person's height: could be any value (within the range of human heights), not just certain fixed heights, Time in a race: you could even measure it to fractions of a second, A dog's weight, The length of a leaf, Lots more! Because continuous data can take any value, there are an infinite number of possible outcomes. Continuous data are data which can take any values. Always remember this: you can't have … Contrast this with discrete data: discrete data is data which is, in short, not continuous. The height of children. Also remember from an earlier Concept how you distinguished between these types of data when you graphed them. Example Ocean currents are continuous data because they can be measured at infinite levels of detail at infinite points in time. These surfaces are characterized by the type or manner in which the phenomenon moves. : you ca n't have … continuous data are data which is an example of continuous data measurements. The difference between highest & lowest observation kind of data is data where the values can continuously. You know this because the data points are not joined takes to sell shoes data set data take. From an earlier Concept how you distinguished between these types of data is often gathered in classes ( height. The number of different values, profits, counts, etc ( like height can! The phenomenon moves data points are not joined you ca n't have … continuous data “ range ” refers the... Are not joined of measurement that would make up a continuous data set, price, profits counts... Not count the number of possible value have … continuous data represent ;! 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