STATISTICS

Statistics



Statistics

Part I

Task 1

This part analyses the sales pattern of ESK jewelers with the help of the data of 1000 sales. To analyze the effect of location on the price of the items sold, here is a plot of the location versus the price of jewelry items.

A bar graph is drawn to see whether the location affects the price of jewelry items sold. Bar charts are widely used to analyze the qualitative data. In a vertical bar chart the vertical axis measures single variable and the horizontal axis can be labeled for different categories of a qualitative variable (Black, 2011). As the data is not time series, we needed a chart type that can show the difference in prices with respect to the location of shop. We have a clear result through this graph that where the shops are located in city, prices are likely to be higher as compare to at the shops located in block or town. Also price of jewelry items at town shops is higher than that of the block shops.

Past market research paper of ESK Jewelers regarded carats as a factor influencing price of the items sold. The data provided on the prices and respective of sold items have the following behavior.

Unlike the previous data set of price according to the location, the data points for carats are continuous therefore a line graph is drawn here. A line graph is best when the variables are continuous and measurable. It does not only show the relationship between two variables but also increasing or decreasing trend can be revealed if any (Francis, 2004). Despite of the fluctuations in curves, the graph represents a trend that jewelry items with heavy carat diamonds are more expensive than those with the low carat diamonds.

When similar kinds of business were analyzed for sales pattern, it has been seen that size of the shop and wealth of the area influenced purchases. In order to check this effect in sales pattern of ESK Jewelers we have made pie charts. This type of chart is helpful when the object is to identify the proportionate sales participation by each category. Pie charts help when the analysis is to be shown visually in a quick glance. They beat work when the values of a variable are few and not close to each other (Czernicki, 2009).

Above is the proportionate sale according to the average home rental per square feet. This variable is taken as a proxy of wealth of the area. The three largest proportions of total sales that are 19%, 15% and 17% were recorded in the area of average rent of $4 per sq. ft. it cannot be concluded that large sales are recorded in wealthier areas as we can see that the area of highest rent, i.e. $6 per sq. ft., participated in only 13% of total sales. Another pie chart to check the proportion in sales according to the size of the shops is as ...