Frequency Distribution
Introduction
The frequency distribution is a conclusion of how often distinct scores happens within a sample of several scores. This implies that a frequency is the general number of times that something takes place. On the other hand distribution basically, refers to the frequencies patterns. Therefore a distribution frequency examines how often particular things takes place within a given values samples (McBurney, & White, 2010). A frequency distribution is an analysis table that is utilized in describing a set of the data set.
The frequency distribution can be described as a representation of either tabular or graphical displays that illustrates the observations number within a specific interval (McBurney, & White, 2010). By utilizing a frequency distribution one can observe the data patterns. In the quest of getting the information sense in a frequency distribution, the data must be organized in a manner that can be easily understood. This is mainly because a frequency distribution table is normally utilized in categorizing data so that it can be interpreted easily and quickly in a way that is visual. A frequency distribution is normally utilized for the purpose of research in order to establish an occurrence of values in the given scores (McBurney, & White, 2010).
Displaying a Frequency Distribution
Through the utilization of the data gathered from a frequency distribution, an individual can then be able to calculate the mode, mean, Standard deviation, range and the median (Rubin, 2010). Frequency distributions are usually illustrated in form of a table format but they can additionally be illustrated using graphical illustrations by the utilization of histograms (Rubin, 2010).
Identification and the Calculation of Mean, Range, Median and Mode
The measures of central tendencies which comprise of the median, mode and mean are often confused (Rubin, 2010). Therefore these central tendencies measures normally contain some differences which are crucial and require high understanding. Mean can be defined as the particular numbers set arithmetic average. The median of a given numbers refers to the central score of those given numbers and on the other hand mode refers to the score that occurs most frequently within a set of particular numbers (Rubin, 2010).
Calculating Mean
The mean of numbers is also referred to as the average which is calculated by adding up all the scores and then dividing the total sum by the number of those scores (Rubin, 2010).
Calculating Median
In the distribution, median is the central score. In calculating median the central score is utilized as the median unless the numbers involve even scores numbers and this, therefore, implies that the central score cannot be established (Rubin, 2010). For instance when the scores set is as follows 3, 2, 2, 6, 7, 9. In this situation since the scores are equal in calculating median, the average of the central scores is used as the median.
Calculating Mode
Because the mode of the score that is most occurring in the frequency distribution, this involves simply choosing the most normal score as the scores mode (Rubin, 2010). For instance, in the following score, the mode can be termed as 1 as it occurs more often in 1, 4, 7, 1, 8, 1 9, 5, 1. Creating a frequency distribution is essential in a situation where there are very man numbers of scores which can be difficult in establishing the mode as well as the median (Rubin, 2010). However, in some scores, there may be two distinct modes which are referred as bi-modal which happen where there are two different numbers which are tied to the frequency (Rubin, 2010).
Applications of Mode, Median and Mean
Every measure of central tendency holds distinct faults and strengths and the selection of the most suitable situation to utilize depends on the presented situation and the mode of attempting t express the given information (Sharma, 2012). In that, the mean of numbers utilizes all the scores in a set in the expression of the central tendency measure whose measure can be altered by the outliers. For instance, a set of very high numbers scores can skew the numbers mean in order for the average mean score to appear in a much higher than the situation of most scores (Sharma, 2012).
In the calculation of median, this measure gets rid of both high and low numbers in a manner that is misappropriated because it does not hold the full capability of representing all the scores in an adequate manner (Sharma, 2012). In reference to mode’s calculation, this may influence in a low level by the outliers and this is a god measure of representing the typical score for the particular numbers group. However, the measure may be of less significance in those cases wherein the scores that have been presented there is no score that occurs twice meaning that the scores mode cannot be calculated (Sharma, 2012).
Conclusion
The use of frequency distribution is essential for statistical evaluation. This is based on two significant reasons which are visualization and inferences. These reasons are useful in defining the general statistics branches which are inferential and descriptive statistics. With the utilization of descriptive analysis such as averages, one is able to comprehend a set of things as the visualization of how scores behave is well illustrated. On the other hand in the section of inferential statistics frequency distribution that is grounded on samples assists in determining the kind of analysis that can be utilized in generating inferences in the context of a presented population. The frequency distribution is also essential as it helps in visualizing particular choices which assist in developing choices thus eliminating the chances of developing wrong decisions.
References
McBurney, D., & White, T. L. (2010). Research methods. Belmont, CA: Wadsworth Cengage Learning.
Rubin, A. (2010). Statistics for evidence-based practice and evaluation. Belmont, Calif: Brooks/Cole.
Sharma, J. K. (2012). Business statistics. New Delhi: Dorling Kindersley.
