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One determinant is what the data will be used for, whether they need to be combined with other data for further analyses. If, for example, you want to study human mortality, you may want to use the same class sizes as for population statistics - which are usually 5-year age bands. That will enable you to calculate deaths rates. However, you may additionally wish to have a band for "less than 1 year" and "1 to 5 years" to allow you to study infant mortality in greater detail. At the other end, you may wish to group together "90 and above".
If there are no such constraints, you should divide up the range of values into 6-10 classes. Ideally, no class should have very few (<5%) observations. If there are, then combine adjoining classes - there is no requirement for the class size to be the same across the whole range.
One determinant is what the data will be used for, whether they need to be combined with other data for further analyses. If, for example, you want to study human mortality, you may want to use the same class sizes as for population statistics - which are usually 5-year age bands. That will enable you to calculate deaths rates. However, you may additionally wish to have a band for "less than 1 year" and "1 to 5 years" to allow you to study infant mortality in greater detail. At the other end, you may wish to group together "90 and above".
If there are no such constraints, you should divide up the range of values into 6-10 classes. Ideally, no class should have very few (<5%) observations. If there are, then combine adjoining classes - there is no requirement for the class size to be the same across the whole range.
One determinant is what the data will be used for, whether they need to be combined with other data for further analyses. If, for example, you want to study human mortality, you may want to use the same class sizes as for population statistics - which are usually 5-year age bands. That will enable you to calculate deaths rates. However, you may additionally wish to have a band for "less than 1 year" and "1 to 5 years" to allow you to study infant mortality in greater detail. At the other end, you may wish to group together "90 and above".
If there are no such constraints, you should divide up the range of values into 6-10 classes. Ideally, no class should have very few (<5%) observations. If there are, then combine adjoining classes - there is no requirement for the class size to be the same across the whole range.
One determinant is what the data will be used for, whether they need to be combined with other data for further analyses. If, for example, you want to study human mortality, you may want to use the same class sizes as for population statistics - which are usually 5-year age bands. That will enable you to calculate deaths rates. However, you may additionally wish to have a band for "less than 1 year" and "1 to 5 years" to allow you to study infant mortality in greater detail. At the other end, you may wish to group together "90 and above".
If there are no such constraints, you should divide up the range of values into 6-10 classes. Ideally, no class should have very few (<5%) observations. If there are, then combine adjoining classes - there is no requirement for the class size to be the same across the whole range.
One determinant is what the data will be used for, whether they need to be combined with other data for further analyses. If, for example, you want to study human mortality, you may want to use the same class sizes as for population statistics - which are usually 5-year age bands. That will enable you to calculate deaths rates. However, you may additionally wish to have a band for "less than 1 year" and "1 to 5 years" to allow you to study infant mortality in greater detail. At the other end, you may wish to group together "90 and above".
If there are no such constraints, you should divide up the range of values into 6-10 classes. Ideally, no class should have very few (<5%) observations. If there are, then combine adjoining classes - there is no requirement for the class size to be the same across the whole range.
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How are probability and statistics related?
Probability is the theoretical basis that underpins statistics.
How is probability related to statistics?
Probability is related to statistics in a direct manner. When one is doing a research for statistics, probability has to be used especially in sampling a small region.
What is the meaning of class size in statistics?
The difference between any two consecutive lower (or upper) class limits it the class width.
Could you suggest a good and unique Maths model for class 9 on any of these topics - Mensuration or Probability or Statistics or Algebraic identities?
rthetj
Who is the father of probability and statistics?
Einstien
What is the symbol for sample size in probability and statistics?
n
Example of a class size in statistics?
25-30 in a class in statistics
How useful probability in statistics?
Statistics is based on the theoretical foundation of probability.
How are probability and statistics related?
Probability is the theoretical basis that underpins statistics.
What subject matter is covered in a mathematical statistics class?
One of the main subjects that is covered in a mathematical statistics class is probability. Another of the main subjects that is covered is making predictions based on trends.
How is probability related to statistics?
Probability is related to statistics in a direct manner. When one is doing a research for statistics, probability has to be used especially in sampling a small region.
Who established the link between probability and staistics?
Statistics is based on probability theory so each and every development in statistics used probability theory.
What is the meaning of class size in statistics?
The difference between any two consecutive lower (or upper) class limits it the class width.
Could you suggest a good and unique Maths model for class 9 on any of these topics - Mensuration or Probability or Statistics or Algebraic identities?
rthetj
Who is the father of probability and statistics?
Einstien
What is differ of mean?
Probability/ Statistics
How does the probability theory apply to statistics?
Statistics is the study of how probable an observed event is under a set of assumptions about the underlying probability distribution.
