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What is the difference between discrete frequency and continuous frequency distribution?

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Discrete frequency is discontinuous -- class interval like 5-10,11-15,16-20,.. like but height of class is same. in continuous -- class interval is 5-10,10-15,15-20, ..like that okay.
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The harmonic mean is a better "average" when the numbers are defined in relation to some unit. The common example is averaging speed. The GM is for situations we want the average used in a multiplicative situation, such as the "average" dimension of a box that would have the same volume as length x width...
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The harmonic mean is a better "average" when the numbers are defined in relation to some unit. The common example is averaging speed. The GM is for situations we want the average used in a multiplicative situation, such as the "average" dimension of a box that would have the same volume as length x width x height. For example, suppose a box has dimensions 50 x 80 x 100 cm. read less
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Discrete data contains finite values that have nothing in- between and continuous frequency data contains data that can be measured that includes fraction and decimals. Example of discrete frequency can be days of a month and in continuous it can be any market value.
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CBSE and NIOS trainer with 20 years of experience also coaching engineering mathematics

Discrete frequency had countable number of random variable (i,e, X=0,1,2,3,...). Continuous frequency had intervals like X greater than 2, X lies between 1 and 3.
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In simple words, discrete frequency occurs at discrete interval(e.g. at 1 sec, 2 sec, 3 sec etc.). But continuous frequency occurs at every point in continuous manner without leaving gaps (e.g. every moment b/w 1 to 2 secs).
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JEE/Board Maths Tutor

Discrete data contains finite values that have nothing in-between whereas continuous data contains data that can be measured, that includes fractions and decimals.
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Definition of Discrete Data: The term discrete implies distinct or separate. So, discrete data refers to the type of quantitative data that relies on counts. It contains only finite values, whose subdivision is not possible. It includes only those values that can only be counted in whole numbers or integers...
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Definition of Discrete Data: The term discrete implies distinct or separate. So, discrete data refers to the type of quantitative data that relies on counts. It contains only finite values, whose subdivision is not possible. It includes only those values that can only be counted in whole numbers or integers and are separate which means the data cannot be broken down into fraction or decimal. Eg: Number of students in the school, the number of cars in the parking lot, the number of computers in a computer lab, the number of animals in a zoo, Number of days in the week etc. Definition of Continuous Data: Continuous data is described as an unbroken set of observations; that can be measured on a scale. It can take any numeric value, within a finite or infinite range of possible value. Statistically, range refers to the difference between highest and lowest observation. The continuous data can be broken down into fractions and decimal, i.e. it can be meaningfully subdivided into smaller parts according to the measurement precision. Eg: Age, height or weight of a person, time taken to complete a task, temperature, time, money, etc. Key Differences: 1. Discrete data is the type of data that has clear spaces between values. Continuous data is data that falls in a continuous sequence. 2. Discrete data is countable while continuous data is measurable. read less
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Discrete data contains finite values that have nothing in- between and continuous frequency data contains data that can be measured that includes fraction and decimals. Example of discrete frequency can be days of a month and in continuous it can be any market value.
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JEE/Board Maths Tutor

Discrete data is countable while continuous data is measurable. Discrete data contains distinct or separate values. On the other hand, continuous data includes any value within range. Tabulation of discrete data, done against a single value, is called as an un-grouped frequency distribution.
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