Executive SummaryFor any business organisation, it is very necessary to be updated about the latest market trends and competitor position. Decisions then shall be taken upon the basis of the statistical analysis that emerges from the data. For this purpose, ALDI collected the data for 4 supermarkets, and analyzed. The various analysis that were done were the analysis of descriptive statistics according to the various supermarkets, the statistics according to the state and statistics according to the location. Descriptive Statistics for various supermarketsThe various descriptive statistics for the different supermarkets is as shown in table 1.SupermarketsSupermarket 1Supermarket 2Supermarket 3Supermarket 4No.
Of Cases30303030Maximum Price91.6588.1591.9562.65Minimum Price77.7777.0077.6659.61Average Price83.3082.1184.4760.43Median Price82.3781.5284.5060.25S. D. of Price3.7310270382.3154543513.3911105730.615465808Kurtosis of Price-0.0987888511.188374162-0.1692901284.372788571Skewness of Price0.8261750820.4048931950.2921201141.510641078First Quartile80.9581.1882.3460.05Third Quartile83.87583.45586.387560.845Range13.8811.1514.293.04Table1. Descriptive Statistics according to the various supermarketsAnalysisAs can be seen from the table, all the types of supermarkets have 30 stores in total. The maximum price is highest at Independent supermarkets. It can be seen that prices at ADLI are significantly lower as compared to other stores. If we compare the mean prices at the various stores, we see that all stores except ADLI have average prices higher than 82, whereas ADLI stores have an average price of just 60.43.
It shall be noted that mean prices are affected by presence of extreme values. The median explains the middle value of the distribution. The median price for supermarket 1 is 82.37, which implies that half of the stores have prices above 82.37 and half have prices below 82.37. The standard deviation of price is the lowest in supermarket 4. The reason for this may be low mean, and a consistent pricing policy amongst all stores.
Another parameter that may be useful in analyzing the variance is the Kurtosis defines the peakedness of a distribution (Levin & Rubin, 2007, pp. 70-71). A higher kurtosis indicates that more variance in the distribution is because of uncommon extreme deviations, rather than common small deviations. We can see that the distribution of supermarket 4 (ADLI) has higher kurtosis value. This implies that majority of the standard deviation in the distribution is because of the presence of an extreme value. To confirm this, we can draw the histogram of the frequency of price for supermarket 4.
This diagram is shown in Figure 1. We can see that there is an extreme value lying between 62 and 63, which might be the cause of majority of the standard deviation. Supermarket 3 is having the lowest kurtosis implying that most of the variation in independent price distribution can be explained by small deviations from the means. The next descriptive statistic that can be observed is the kurtosis and skewness of the price distribution. Skewness is an assessment of the asymmetry of the distribution of the given construct.
A negatively skewed distribution implies that that the variable is skewed towards left, and the number of observations that are higher is greater than the number of lower observations. If we see the skewness values for all the 4 supermarket categories, it can be implied that all are skewed towards the right. This implies that they have more number of smaller values than higher values. This can again be confirmed by having a look at the frequency histogram of the price. For example, let us take the histogram for supermarket 1.
The graph for the same is in Figure 2. It can be clearly seen that the distribution of the variable price is skewed towards right, and the tail is longer at the higher end of the distribution.