Descriptive for Restaurant Group, Burger King Worldwide, Breadtalk Group - Statistics Project Example

COMPUTER BASED PROJECT Sur Sur First org; Second org; -In this paper, we study the behavior and patterns of monthly oil prices from 3rd June 2013 to 1st May 2014. It is evident that the stock quote values have been very volatile over this period of time with for all the restaurants under the study. It is also evident that due to the volatility of these stock quotes, the data sets are far from following a normal distribution. The shapes of the histogram, values of kurtosis and skewness further confirm our fear as to whether the data sets follow a normal distribution. Introduction Forecasting is both a Science and an Art. It is capable of recognizing patterns by use of logical and analytical methods. With forecasting, managers and economists are able to understand and predict the future (Makridakis & Wheelwright, 1989). The objective of this project is to identify particular data features, and to comment on it. Data The data was a daily time-series spanning from 3rd June 2013 to 1st May 2014. The data relates to stock quotes of four different restaurants in Germany, United Kingdom, USA and Singapore. A total of 239 days (observations) were collected for each case in this study. Descriptive Statistics a) SOUP RESTAURANT GRP (SR.6F) We begin by looking at the descriptive statistics of the data. The stock quotes are categorized into open, low, high, close and adjusted close, we will however consider the adjusted close. The mean adjusted close is computed to be 0.113 with a standard deviation of 0.024 (with a variance of 0.001); this implies that there is small variation from the mean. To affirm the small variations from the mean, we look at the minimum and maximum values adjusted stock quotes; the minimum price of oil is computed to be 0.07 while the maximum price is computed to be 0.160, this shows a very small range in the data (stock quotes) for the given period of time. The value of skewness is -0.665, a value less than zero; this implies that the data (stock quotes values) has a left skewed distribution and that most values are concentrated on the right of the mean (greater than the mean), with extreme values to the left. Kurtosis is given as -1.001 Read More