Regional Location of Slender Vision Ltd Outlets - Essay Example

Assignment Task Slender Vision Ltd (SVL) is one of the large company selling Flat screensfor computers. It has many shops throughout the United Kingdom (UK). Most of the shops are located in the regions: North, South and East of the UK. There are a total of 105 outlets. Three types of screens are predominately sold (Type A= 12inches, Type B= 15inches and Type C= 19inches). In this study we are using total sales data together with other useful information that is stored by the assistant managing director of SVL. Here we are doing Statistical analysis on that data. Regional Location of SVL Outlets From the frequency table and Pie chart it comes to know that there were 39% of the SVL outlets are in South region, 34% are in North region and the remaining 27% of the outlets are in the East region. The frequency table shows that numbers of female managers are more than male managers in SVL outlets. Descriptive Statistics of Different types of SVL flat Screens The descriptive statistics and the bar chart shows here annual sales of SVL 12”, 15” and 19” flat screens of computers, the chart shows that the annual sale of Type C screens that are 19” are greater than sales of type B and type a it is obviously because the 19” screens are expensive than 12” and 15”. Association between Distance of SVL outlets from High Streets and Total Sales Correlation The correlation is one of the most common and most useful statistics. A correlation r is a single value that explains the degree of relationship among two variables. Correlation value r will always be between -1.0 and +1.0, if the correlation is negative, we have a negative relationship; if its positive, the relationship is positive. Here we have the correlation value r = -0.786 and the scatter plot shows a negative association between distance of SVL outlet and the Total sales in SVL outlets, it means the sales in SVL outlets that are near to high streets is more than in those outlets that are far from the high street. Association between Average Monthly Advertising Expenditure and Total Sales The correlation value r = 0.772 and the scatter plot shows a positive association between average monthly advertising expenditure and the Total sales in SVL outlets, it means the sales in SVL outlets increases with the expenditure on advertising. Regression Regression investigates the dependence of one variable conventionally called the dependent variable on one or more variables called independent variable and provide an equation to be used for estimating or predicting the average value of the dependent variable from the known values of independent variable. The regression procedure fits the model: Y = a + (b x X) + e Where, Y is the predictor, X is the predictor, “a” is the value of Y when X equals zero and is called Y-intercept, and “b” indicates the changes in Y for a unit change in X and is called the slope of the line and “e” is an error term having a normal distribution with mean of zero and standard deviation σ (Fisher, 1922). We estimate “a” by “a”, “b” by “b” and “σ” by “s”. The fitted equation is then: Where, is called the predicted or fitted value, “b” is the slope of the line known as regression coefficient and “a” is known as y-intercept. Y = a + b X Y-intercept = 499.078 Slope = 0.248 Y = 499.078 + (0.248)X The estimated regression coefficient b = 0.248 indicates that the values of Y change by (0.248) units for a unit increase in X. If we want to know the total annual sales if the SVL spend £ 300 in monthly advertising expenditure then we have the total annual sales: Y = 499.078 + 0.248(300) Y = 573.478 (£000s) ANOVA Here we are doing hypothesis testing on the given data, in order to find the impact of regional location and impact of gender on the total sale of SVL flat screens of computers. 1. Ho: There is no significant difference of regional location of SVL outlet on the Total Sales of SVL Flat Screens of Computers H1: There is a significant difference of regional location of SVL outlet on the Total Sales of SVL Flat Screens of Computers  = 0.05 Regional Location Decision: If we have P-value <  then we have to reject our hypothesis, from ANOVA table of regional location and total sales in SVL outlets we get the P-value = 0.810 that is greater than  = 0.05, so here we don’t reject our hypothesis and conclude that there is no significant effect of regional location on the sales at SVL outlets. 2. Ho: There is no significant difference of gender of SVL manager on the Total Sales of SVL Flat Screens of Computers H1: There is a significant difference of gender of SVL manager on the Total Sales of SVL Flat Screens of Computers  = 0.05 Gender of Manager Decision: From ANOVA table of gender of SVL manager we get the P-value = 0.439 that is greater than  = 0.05, so here we don’t reject our hypothesis and conclude that there is no significant effect of gender of SVL manager on the sales at SVL outlets. Conclusion The following results were obtained after the analysis: 1. Highest numbers of SVL outlets are in South. 2. Most of the managers in SVL outlets are females. 3. The highest annual sales are of 19” flat screen of computers. 4. Nearest outlets from high street and annual expenditure on advertising both are beneficial for the significant raise in the annual sales of SVL flat screens. 5. ANOVA shows that there is no significant effect of regional locations and gender of managers on the total sales of SVL flat screen outlets. Task 2 Apple used 13 million pounds of e-waste in the year 2006 that is equal to 9.5 percent of the weight of all goods Apple sold seven years past. Apple expects that this percentage to grow to 13percent in year 2007, and to 20 percent in 2008. By 2010, it is to be forecasted that Apple will recycle 19 million pounds of e-waste per year; here is the graph of current and forecasted present below. Weight Recycled as % of Past Sales The graph shows that the there is a continuous improvement from the year 2002 to 2007 and it is predicted that it will be grow further in coming years. Read More