If you were in the diamond business, you would have to know how to price diamonds accurately otherwise you would either be losing money (selling too cheaply) or losing customers (selling too expensively.) Many people buy diamond engagement rings and it is often insignificant personal purchase in fact, buying a diamond and buying a house or similar in two ways. Both the house and diamond can be significant investments of your heart and money no to our exactly like unlike two new cars so you can't just shop around and clearly see who has the best price. So having some sort of price really can be very useful for a lot of people in this lesson impact building the ruler based on data. read about the four seas of diamonds, cut clarity, color and carrot weight for some background information with this data. You will have a pretty good idea of what size diamond you can afford and you will know whether diamond you see jewelers is worth the cost. imagine you've set out to purchase a diamond and you want all the information you can possibly get before the purchase you run down Internet search on diamonds to learn more about the different cuts Car rangers color values and so on after having a research to bet you, you decide on the basic cut quality color and weight range that you can probably afford. this diamond pricing spreadsheet gives three snapshots of a large set of data on diamond pricing the 0.30 0.40 carrot tab gives a 2012 data on diamonds raging from 0.30 0.40 carrots. go to the subset tab, which gives us subset of randomly chosen data from the first time go to your math tools and open the graph to apply the date of weight carrot versus pricing this tab using the plus data button note that you can copy two columns of data use paste table data.

Part B What can you say about the relationship between the price and the weight? BI U X X2 15px A The price and weight of this graph is very random, The data is random and the of the diamond varied based on weight and clarity. The variation in the data w Space used (includes formatting): 317 / 15000 Part C What can you say about the slope of the regression line