A jewelry firm wants to submit a bid to purchase a large collection of diamonds but is uncertain how much it should bid. You will use the results from a predictive mod

Assignment Overview 

A jewelry firm wants to submit a bid to purchase a large collection of diamonds but is uncertain how much it should bid. You will use the results from a predictive model to make a recommendation on how much the jewelry company should bid for the diamonds. 

Assignment Details 

A diamond distributor has recently decided to exit the market and has put up a collection of diamonds up for auction. Seeing this as a great opportunity to expand its inventory, a jewelry firm is interested in making a bid. To determine how much to bid, the firm’s analytics department will use a large database of diamond prices to build a linear regression model to predict the price of a diamond based on its attributes.  

As the business analyst, you are tasked to build the linear regression model and apply that model to make a recommendation for how much the company should bid for the entire collection of diamonds. 

Assignment Submission 

To complete this assignment, you will be submitting a file in Word using a report format to provide the answers to the following questions across five steps. 

Step 1 – Research and Reflect: 

Recent news reports have highlighted growing concerns about the value of diamonds, as technological advancements in creating simulated diamonds have made them nearly indistinguishable from their mined counterparts. These lab-grown diamonds possess identical physical, chemical, and optical properties to natural diamonds, leading to increased debate about the future of the diamond industry. As the production of synthetic diamonds becomes more cost-effective and environmentally friendly, the market may shift, potentially impacting the value and demand for traditionally mined diamonds.

There is also concern regarding the perception of the value of simulated diamonds versus traditionally mined diamonds which could lead to potential confusion and devaluation in the market. As the quality and affordability of synthetic diamonds increase, some consumers may question the rarity and exclusivity traditionally associated with mined diamonds. Additionally, the ethical and environmental issues surrounding diamond mining may further drive the preference for lab-grown alternatives. This shift in perception could ultimately impact the value and demand for mined diamonds, leading to potential disruptions in the diamond industry.

Consider the ethical and environmental concerns presently surrounding diamond mining and in no less than 500 words, answer the following question: Can the diamond industry effectively communicate the value proposition of mined diamonds to maintain consumer demand and differentiate them from the simulated alternatives? If so, how? If not, why not?

Use what you learned from Part III of Drucker’s book (Managing for Results) to help support your argument.

Remember to cite your sources.

Step 2 – Understanding the Model: 

There are two datasets. 

• "Diamonds" contains the data used to build the regression model. Download "Diamonds" contains the data used to build the regression model. 
• "New Diamonds" contains the data for the diamonds the company would like to purchase. Download "New Diamonds" contains the data for the diamonds the company would like to purchase. 

[NOTE: Click on the link above to assess the dataset] 

Both datasets contain carat, cut, and clarity data for each diamond. Only the diamonds dataset has prices.  

• Carat represents the weight of the diamond and is a numerical variable. 
• Cut represents the quality of the cut of the diamond, and falls into 5 categories: fair, good, very good, ideal, and premium. Each of these categories are represented by a number, 1-5, in the Cut_Ord variable. 
• Clarity represents the internal purity of the diamond, and falls into 8 categories: I1, SI2, SI1, VS1, VS2, VVS2, VVS1, and IF. Each of these categories are represented by a number, 1-8, in the Clarity_Ord variable. 

Using Excel (or other application with which you are familiar), build the linear regression model using the diamonds dataset. 

1. Based on the Summary Output produced by the regression analysis write out the linear regression model and explain why you are confident (or not confident) in the model to predict the price. NOTE: Copy and paste the summary output into your report. 
2. According to the linear model, if a diamond is 1 carat heavier than another with the same cut and clarity, how much more would the retail price of the heavier diamond be? Why? 
3. If you were interested in a 1.5 carat diamond with a Very Good cut (represented by a 3 in the model) and a VS2 clarity rating (represented by a 5 in the model), what retail price would the model predict for the diamond? 
4. Does color effect the price of the diamond? If the color code of the diamond specified in part 3 is H, I, or J, how much cheaper or more expensive will this diamond be compared to any other color of the same diamond? 
5. Does the regression model estimated in part 4, produce residuals that are normally distributed? Explain your answer; you may use a graphic to support your explanation. 

Step 3 – Calculate the predicted price for each diamond: Using the new diamonds dataset, for each diamond, plug in the values for each of the variables into the linear model (equation), then solve the equation to get the estimated, or predicted diamond price. Note: For this step, simply use the model developed in part three, which does not include the color code information.  

Step 4 – Visualize the Data: Create two scatter diagrams (or scatter plot).  

• Plot 1 – Plot the data for the diamonds in the database, with carat on the x-axis and price on the y-axis. 
• Plot 2 – Plot the data for the diamonds for which you are predicting prices with carat on the x-axis and predicted price on the y-axis. 
• Note: If you know how, you can also plot both sets of data on the same chart in different colors. 

1. What strikes you about this comparison?  
2. After seeing this plot, do you feel confident in the model’s ability to predict prices? Why or why not? 

Step 5 – The Recommendation: Now that you have the predicted price for each diamond, it’s time to calculate the bid price for the whole set. Note: The diamond price that the model predicts represents the final retail price the consumer will pay. The company generally purchases diamonds from distributors at 70% of that price, so your recommended bid price should represent that. What bid do you recommend for the jewelry company? Please explain how you arrived at that number.  

(CLO 1,4,5) 

Most classes have a 2 paper requirement per course. Please be sure to address the following requirements when completing your papers:

•  The cover page and reference page/s are not included in the above-stated page requirement. These should be in addition to page requirements.
•  Papers need to be formatted in proper APA 7th Edition style.
•  Each paper requires a minimum of at least three outside peer-reviewed sources for your references (unless stated otherwise in the guidance above).

o   Acceptable/credible sources include: Academic journals and books, industry journals,  and the class textbook.   To include additional types of sources, please review the “Guidelines for finding and utilizing required references for your paper,” shared below.

•  Using your textbook is highly recommended to demonstrate that you have read the required material and/or are connecting new thoughts to the course text/learnings.

Guidelines for finding and utilizing required references for your paper:

For a formal research paper, you are required to locate, understand, and integrate a certain number of peer reviewed journal articles and/or published books, as these are considered reliable and valid sources of information by academics and industry.  The best source of these articles is to search through your CiAM Library (LIRN).  However, if you find a website you would really like to share in your paper, you can do so if it is NOT counted as one of your reliable/valid articles/books (i.e., goes above and beyond the required amount of reliable/valid sources), and if it is NOT the basis/foundation of your paper.  Otherwise, there is no way to demonstrate that:  1.  You have done true research and have given the appropriate level of thought to your paper; and 2. There is no way to validate that the information you have received off of the internet has been fact checked. 

Here are some guidelines on how to think about this process:

1.  Using Wikipedia:  This internet source is very popular, and although there may be some great articles found there, there is no formal process (at this point) for what is posted to be fact checked.  Meaning, what you find there is not always true.  However, if you read an interesting article, you can go to their references, check on who they researched, then go to that ORIGINAL work (locate it in our library), and then read through that article and reference that article (not Wikipedia).  If you want to cite Wikipedia, you may do so if it follows the guidelines shared above (i.e., is NOT the basis of your paper, and is just a supplemental share going above and beyond the minimum required reliable/valid works).  You may also simply visit Wikipedia just to get more general information on a subject before you start your formal research process).

2.   General informational websites and business websites:  These follow the same rules as shared above.