Continuous Data

Continuous data refers to data that can be measured on a measurement scale with other data. It is also known as variable data and can be subdivided into smaller measurements limited by the recording or measurement system. It can have any numeric value and can be divided into precision.

Continuous data refers to information or data that are used to calculate a measurement scale or continuum along with other data. Also known as variable data, it can easily be subdivided into precise increments but on depending upon the requirement of the system of measurement.

Unlike the discreet data that helps to measure like bad or good, on or off, etc, the continuous data can be put to record at numerous points (temperature, width, size, length etc.). Example for discreet data is the number of students in a class who can be 50, 60 etc but not 50.5 or so whereas continuous data example is the height of the students which can be anything between the two digits like 5.55 or 6.87 or so. There are two types of continuous data:

Unlike the discreet data that helps to measure like bad or good, on or off, etc, the continuous data that you can very easily record at numerous points

• Physical Property Data: Physical property data refers to the physical aspects of a process for instance - weight, temperature, height, width and length. All such data can be divided into smaller precise measure. A kilogram can be divided into grams.
• Resource Data: Resource data can be referred to those that details or measures the assets related to a process such as money or time. Furthermore, both money and time can be subdivided into minute measures.

The resource data and physical data are categorized as continuous data because they can be measured on a precise and smaller scale. With the measurements, you can use that information for further reference or process.

Data can be continuous especially in range of values or in geometry. For a particular data, the range of values can have a minimum or a maximum value. So, it can even be a value in between. For example: if you measure the size of a coin and it measures 25mm. With precise specification, the coin should not be bigger than the measure of 27 mm and also be least 25 mm. Furthermore, if you count the available number of coins that are bad vs. good then it is called the collection of attribute data. On, the other hand, if you measure each coin and note down the sizes such as 25.2 mm, 26.3 mm, 27.6mm, etc. that can be regarded as continuous data. So, you actually avail more details or information pertaining to what you are measuring from the continuous data rather than from the attribute data. For a particular data the range of values item has a maximum and also the minimum value but the continuous data can also be any value in between.

You will realize the vitality of how data should be measured as you transform data into information. And six sigma measurement practices usually refer to the type of data which you will have to choose and to be measured within a process for better results. Before choosing data for six sigma, you should be extra cautious and keep in mind that it is important as it will indicate the seriousness and size of the hassle or problem in the course, you are investigating and also it will indeed be valuable and helpful to perk up the particular process. While collating data, different measures are adopted. In this process, the different types of measures are the length of the process, period to execute, the dimension on a product or the count of defects spotted in a day. If a person decides to calculate or measure he/she should understand the importance of data to be measured in an accurate manner.

It is also necessary to know discreet data in order to understand continuous data precisely. Discrete data is the absence or presence of some features in each device under the method. The discreet data can be classified into three types:

• Characteristic Data: It details the feature of a process.
• Count Data: It depicts the frequency or number of an observable event that take place in a process. It is generally used to measure defects.
• Intangible Data: It illustrates or describes a particular piece of process that is vague or intangible. For instance. Feelings cannot be measured in physical measures but it might be measured on the base of good to bad or low to high. Thus, intangible data helps to measure or determine on a scale of 1-5 as business customers’ satisfaction.

The continuous data like discreet data has pros and cons. The advantage of continuous data is that any value and not a limited set of value are possible with the specific range. For instance, when measuring height of child, using a discrete data can give set of possible values. A continuous set of possible values allow you a more precise and exact measurement. The demerit is that no two data values may be the identical, and so no mode. It would make any type of probability calculations impossible since there is infinite number of possible values.