WebCab Probability and Statistics for COM v3.3 Demo

GroupedData Class

Within this class we consider the study of Grouped Data.

For a list of all members of this type, see GroupedData Members.

System.Object
   GroupedData

public class GroupedData

Remarks

In particular, we allow quantitative measures of a Grouped Data set such as its Sample Mean, Sample Variance and Samples Standard Deviation to be evaluated.

Example of a Grouped Data Set

In order to assist in the analysis of a given data set it is often convenient (and in fact often necessary) to collect the data into categories. For example, consider a data set which consists of the heights of a set of 100 people. Now in order to derive qualitative properties concerning this data set it is natural to group the data set into height intervals (i.e. such intervals could be 0m - 1.20m, 1.21m - 1.50m, 1.51m - 2.00m, 2.01m - 3m. For each interval the number of members (i.e. frequency) of the original data set which fall within the interval would be recorded.

Applying this class

If order to apply this class you will first need to register the group data set, after which you will be able to apply the available business methods.

Registering the Grouped Data Set

Whenever applying this class you will need to first register (i.e. set) the grouped data set from the present instance. This is done by calling:

  1. SetMidpoints - Register the set of midpoints of the grouped data.
  2. SetFrequencies - Register the frequencies of the classes within the grouped data.

Calling the Business Methods

Once the grouped data set has been registered you are able to evaluate:

  1. SampleMean - The Sample Mean of the Grouped Data.
  2. SampleVariance - The Sample Variance of the Grouped Data.
  3. StandardDeviation - The Standard Deviation of the Grouped Data.

Remark: Each one of the above measures of a grouped data set can be thought of as an approximation of the corresponding measure of the underlying data set. The reason for this is that the midpoint of each class can be thought of as an approximation of the mean of the class, and the distance from the midpoint to the mean is an approximation of the distance from each member within a class to the mean of the entire data set.

Requirements

Namespace: WebCab.COM.Statistics.Statistics

Assembly: WebCab.COM.StatisticsDemo (in WebCab.COM.StatisticsDemo.dll)

See Also

GroupedData Members | WebCab.COM.Statistics.Statistics Namespace