Applied Statistics: Frequency Distribution

Applied Statistics: Frequency dissemination

Frequency scatterings are yet another technique by which statistics can simplify large quantities of information. This method typically groups or classifies data in order to more clearly capture certain information.

The construction of a frequency distribution is somewhat simple. First, it is necessary to determine the come of classes that will be apply to group the data. Second, the data mustiness be sorted into these classes. Third, the number of items in each class must be counted. The closing step in creating a frequency distribution involves displaying the results in either a chart or a table.

The write media commonly make use of frequency distributions. Newspaper and cartridge holder articles often include both charts and tables. Just maven example would be the display of election returns. Obviously this data is comprised of numerous ballots. To make the ballots more comprehensible, frequency distributions are created. This process involves numeration the ballots and subdividing the votes. The frequency distribution then shows the number of votes received by each candidate.

Unfortunately, while frequency distributions present data in a relatively compact form, there are ordinarily some types of information that can only be obtained from the current data. Therefore, although frequency distributions allow data that is more usable, they do so at a price. While certain information must be lost, this ultimately provide

mayhap the most widely used and quoted cant overed average is the Dow Jones industrial average. This financial average is comprised of 30 of the biggest and best-known American stocks. from each one stock's contribution is weighted according to its per-share closing price. Thus, a companionship whose stock sells for $100 per share has twice as some(prenominal) potential influence over the Dow Jones industrial average than one whose stock sells for $50 per share. This characteristic has long been a bloodline of criticism.

As defined by Simon & Freund (1991), the " way is the honour which go bys with the highest frequency." The mode is perhaps the simplest of the so-called averages to derive. In fact, the figure requires no counting whatsoever. Finding the mode of a given set of data requires only that the statistician count the different value. Grouping the values according to frequency will then delineate that value which predominates.

Normal distributions are used primarily for quantities that are mensural on a continuous scale (e.g., the net weight of a food or the speed of a car). They provide a method by which the probability of phenomena may be assessed. Hence, they could, for example, be used to predict the likelihood of an earthquake.

In addition, the suppose of a population of N items is defined similarly:

data following a normal distribution typically occur under a symmetrical bell-shaped curve. This curve shows the distribution of probability associated with different values of some random variable. In theory, such a curve would extend indefinitely in both directions. These "tails," however, generally become negligible when carried out out from the mean more than four or five criterion deviations.

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