Introduction:

Cumulative frequency is a statistical measure used to determine the number of observations that fall below a particular value in a dataset. It is an important concept in statistics that helps to analyze and interpret data in a meaningful way. In this response, we will discuss whether cumulative frequency only refers to the less-than type, more-than type, or both.

Cumulative Frequency:

Cumulative frequency is a statistical tool that helps to analyze the distribution of data. It is a measure of the total number of observations that fall below a particular value in a dataset. Cumulative frequency is calculated by adding up the frequencies of all the values up to a certain point. It can be represented in a cumulative frequency table or graph.

Less-than Type Cumulative Frequency:

Less-than type cumulative frequency is a type of cumulative frequency that counts the number of observations that are less than or equal to a particular value in a dataset. It is the most commonly used type of cumulative frequency and is represented in a cumulative frequency table or graph. In a less-than type cumulative frequency table, the frequency of each value is added to the frequency of the previous value until all the values have been accounted for.

More-than Type Cumulative Frequency:

More-than type cumulative frequency is a type of cumulative frequency that counts the number of observations that are greater than or equal to a particular value in a dataset. It is less commonly used than less-than type cumulative frequency but can be useful in certain situations. In a more-than type cumulative frequency table, the frequency of each value is subtracted from the total frequency until all the values have been accounted for.

Conclusion:

In conclusion, cumulative frequency can be both less-than type and more-than type. However, less-than type cumulative frequency is the most commonly used type in statistical analysis. Both types of cumulative frequency can be represented in a cumulative frequency table or graph and can provide valuable insights into the distribution of data. It is important to understand the differences between less-than type and more-than type cumulative frequency and when to use each type depending on the nature of the dataset.