Wal-Mart stores Inc., is the second largest company following ExxonMobil. It has stores in all the 50 states of the United States, which are operated mainly through supercenters, Neighborhood market and stores offering discounts (About, 2008). The company was found in 1962 by Sam Walton an entrepreneur in Arkansas with the aim of targeting the low income earners through slashed prices. In 1999, the company made its break through move by expanding beyond Mexico into the United States. By 1986, the super chain had made tremendous moves to increase its income; the company had completed a network for its satellite which enabled the company to track inventory (Hoovers, 2004). In addition efforts, to aid inventory at the local level, the company equipped almost all its stores with barcode readers.
The company has reported tremendous profits even in times of economic crisis. While many companies were reporting a downfall in sales, the company was reporting a sales growth of 11%. In its financial report back in 2003, Wal-Mart stated that its sales in international division had surpassed 40 billion dollars, and increased by more than 15% compared to its previous years (Wal-Mart, 2005).By expanding internationally, the company was able to acquire a mass market that led to a drastic increase in its sales. Most of its suppliers operate at a global level. In connection with this, the company is able to bargain for larger discounts in the goods it purchases from its suppliers, which reduce its expenditure.
From the track record of Wal-Mart, it is clear that the biggest US retailer has grown tremendously over the past 40 years. Through strategic operation, such as its international strategy, the company remains a leader and an example to many other companies operating in the same field. In recognition of its effort, this paper engages in a descriptive analysis of Wal-Mart Company`s revenue. In other words, this paper, deals with a series of descriptive statistics for the company. Through descriptive statistics, the paper uses a mathematical approach to interpret and summarize some aspects of the datasets in regards to the super chain’s revenue. The paper then makes a conclusion in regards to the properties from which the datasets were drawn. The major aim of the paper is to identify emergent trends in the datasets through the concrete description and summary of the dataset. The descriptive statistics will enable us to discern the trends in the revenue of Wal-Mart. Descriptive statistics does not give us an opportunity for conclusions beyond the analyzed datasets i.e. descriptive statistics will not employ conclusions for the hypotheses we make from the datasets. In describing the data, the paper will mainly concentrate on the two general types of statistics used in data description: the measure of spread and the use of the measure of central tendency.
The datasets used in the analysis mainly consist of the quarterly performance of Wal-Mart Company over an 8 year reach beginning in 2001 and ending in 2008. The paper will begin with a brief definition of variables, and then continue to define the nature of the variables used. In the background, the paper has given a thorough analysis of Wal-Mart Inc. with the aim of forming an understanding of the information in the datasets. Subsequently, the paper will proceed with a year to year descriptive analysis of the variables of Wal-Mart revenue. The revenue variables will be the key characteristics of interest in the data sets. They are the measurable quantities that show the difference between characters in the Wal-Mart revenue. Generally, variables are either discrete or continuous. Discrete variables take the form of fixed and countable values, e.g. in a data set for a certain population, the discrete variables consist of factors such as gender, race. On the other hand, continuous variables consist of factors such as height, age, weight, income, revenue. The dataset on Wal-Mart revenue consists of continuous variables. Continuous variables have intervals that are fixed and that are clearly separable between adjacent values. Unlike the discrete variables, continuous variables can be mathematically manipulated. In descriptive statistics, continuous variables such as the one on Wal-Mart revenue are described using 3 classes; location statistics, dispersion statistics or shape statics. In this paper, we will mainly concentrate on these classes to provide a description of the data.
Firstly, we will use location statistics; this uses of the mean, median, mode and quintiles. The mean, median and mode are the measures of central tendency. The mean represents the middle number; in statistics, the larger the size of the sample the more reliable will be the mean. The mode will be the most frequent number. The second form of description will be the application of dispersion statistics; variance, standard deviation, range, interquartile range. Dispersion statistics will be helpful to give information on how the data varies from the central tendencies. The range will give a difference between maximum and minimum values. Dispersion about the mean will be quantified by the variance or the standard deviation from the mean. Thirdly, the paper will use shape statistics by measuring the skewness or the distribution shape of the variables. Skewness will either be symmetric or asymmetric. A symmetric shape size arises when the skewness is equal to zero; mainly when the mean and median are equal. An asymmetric skewness arises when the tail is pronounced in one side more than the other. After describing the data, the paper will explain the description mainly by discerning trends and making conclusion in regards to the inferred data.
As stated earlier, the dataset consists of the per quarter revenue data from the year 2001 to the year 2008. In the first year, the year 2001, descriptive analysis used location statistics to find the mean revenue for the four quarters. The mean revenue for year 2001 was 47.85; in addition, location statistics was applied in finding the median for the year. The median for the year 2001 was 45.9. Further, dispersion statistics was used to find the variance and the standard deviation for the year. The variance for the year 2001 was 26.94, while the standard deviation was 5.19. Dispersion statics was used to find the range for 2001 revenue, i.e. the difference between the maximum and the minimum revenues in the year. The range in the four quarters of 2001 was 13.6. In applying shape statistics, since the mean and the median were not equal, the skewness of the data was asymmetrical.
In the year 2002, location statistics was used to find the mean and the median. The mean revenue figure across the four quarters for 2002 was 54.48. The median for 2002 revenue was 52.55. In order to get information on how the data varied from the measures of central tendency, the analysis applied dispersion statistics on the revenue for the year through application of the range, variance and the standard deviation. The range for the four quarters was 15.6. The variance for the year was 34.40, while the standard deviation for the year was 5.87. Since the mean and the median were not equal, the symmetry could not be zero and, therefore, the skweness for the shape statistics for the revenue of the year was asymmetrical. In the four quarters for the year 2003, description firstly entailed application of location statistics through the mean and the median. The average revenue for the four quarters in 2003 was 61.15, while the middle number was 52.55. Application of dispersion statistics utilized the concepts of variance, the range and the standard deviation. The range across the four quarters in the year was 16.1. On the other hand, the variance for 2003 was 35.95. The standard deviation for the year was 60. The skewness for the year was asymmetrical.
For the four quarters in the year 2004, the mean revenue amounted to 64.05. The median for the year was 59.25. In applying dispersion statistics, the range for the year was 17.8. On the other hand, the variance for the year was 42.86. The standard deviation for the year was 6.48. The application of shape statistics revealed an asymmetric shape in the skewness, since the mean and the median were different and could not equal zero. For the year 2005, the first description was through the application of location statistics. The mean and the median across the four quarters in the year 2005 were 71.3 and 69.1 respectively. The maximum revenue and the minimum revenue for the year differed with a 17.4.
In regards to the difference from the measures of central tendency, the variance for the year amounted to 42.86 while the standard deviation was 6.5. In the year 2006, the mean for the quarters was 74.1. The median for the year 2006 was 76.1. On the other hand, the variance for the year was 40.37. The standard deviation for the year was 6.9. The revenue had an asymmetrical shape. Description of the year 2008 began with the application of location statistics. Firstly, the average for the quarter’s revenues in the year was calculated and amounts to 93.45. The middle number for the quarters in the year was 91.05. On the other hand, in application of dispersion statistics, the range for the quarters was 20.9. The variance for the revenue in the year was 60.37, while the standard deviation for the year was 7.77. Lastly, in application of the shape statistics for the year, the skewness of the data was asymmetrical.
From table 1, and graph 1, it is clear that the mean revenue has taken an annual increase from the year 2001 into subsequent years. It can be hypothetically stated that Wal-Mart revenues have taken an increasing trend from the year 2001-2008. This hypothesis can be explained through the company’s tremendous efforts to increase its revenue. The company has expanded to new markets and adopted international strategies to increase its revenue. These revenues were reflected in its 2003 financial report, Wal-Mart reported that its sales in International Division had surpassed 40 billion dollars, and increased by more than 15% compared to its previous years. Further explanation of the increasing trend can be given by the company`s ability to become a retail leader in all the 50 states of the US. The company has grown in popularity in the recent decade to become the preference market for 84% of the American population. Annually, the company is visited by more than 176 million people.
The company has strategically benefited from its ability to operate at a global level. Apart from the US market, the company has ventured into other countries such as Korea, Japan, Brazil and China. By expanding internationally, the company was able to acquire a mass market that led to a drastic increase in its sales. Most of its suppliers operate at a global level. In connection with this, the company is able to bargain for larger discounts in the goods it purchases from its suppliers. Further, using the standard deviation, it is easy discern revenues that are normal, extra large and extra small. The standard deviation is taking an increasing trend over the subsequent years from the year 2001.
In conclusion, the data analyses of Wal-Mart revenue shows a clear trend emerging from the revenues of the company. The revenues have been increasing by every quarter. Further the mean revenues per year have increased annually. This trend is reasonable and offers an actual reflection of the sales of the company.