MBA FPX 5008 Assessment 2 Using Analytic Techniques to Add Meaning to Data
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Assessment Overview:
MBA FPX 5008 Assessment 2: examines Amazon’s business performance and stock data using logical ways. By interpreting deals data by member, stock price trends, and trading volume, the analysis demonstrates how graphical and statistical styles give meaningful perceptivity. Amazon’s growth ine-commerce and pall services highlights its dominance in the request and the effectiveness of using analytics to estimate performance and trends.
How to Pass MBA FPX 5008 Assessment 2 Using Analytic Techniques to Add Meaning to Data
To ensure you successfully demonstrate your ability to add meaning to data using analytic techniques, focus on these 10 points:
- Clean Up Technical Terms: Your source text contains several OCR/scan errors. Ensure you write “innovated” as “founded,” “member” as “segment,” and “standard” as “median” where appropriate for statistical accuracy.
- Define Your Terms: Don’t just list the numbers. Briefly define what the Mean (average), Median (middle point), and Mode (most frequent) represent in the context of Amazon’s stock.
- Interpret Volatility: Pay special attention to the Standard Deviation ($141.98). Explain that this number measures how much the stock price “spreads out” from the average, indicating the level of risk or stability.
- Distinguish Between Histograms and Scatterplots: Clearly state that the Scatterplot was used to show a trend over time, while the Histogram was used to show the distribution (frequency) of prices.
- Analyze the AWS “Profit Engine”: Note that while Online Stores account for 53.01% of sales, the text mentions Amazon relies on AWS for actual gains. Explain this discrepancy between high revenue and high profit.
- Address the Volume Statistics: In your draft, ensure you fill in the “Mean daily stock traded volume.” The prompt left this blank, so you should describe it as a measure of market liquidity (how easily the stock is bought/sold).
- Use Visual Language: When describing the scatterplots, use terms like “positive correlation” or “upward trend” if the stock price increased from April 2019 to April 2020.
- Connect to Business Strategy: Relate the data back to Amazon’s “customer-centric” mission. Explain how high trading volume and stock growth reflect investor confidence in that mission.
- Check the X and Y Axes: When describing your charts, explicitly state what is on each axis (e.g., “Date on the X-axis and Price on the Y-axis”) to demonstrate you understand graphical construction.
- Verify References: Ensure the link for The Balance Careers (Schneider, 2019) is correct and not a duplicate of the Amazon Investor Relations link. Use consistent APA formatting.
Sample Assessment:
Amazon: The Retail Behemoth
Amazon, a Fortune 500e-commerce company, was innovated in 1994 by Jeffrey Preston Bezos. Firstly an online bookstore, it snappily expanded its immolations to a wide range of products and services. By 1999, Bezos was named Time magazine’s “ Person of the Time, ” emblematizing the rapid-fire success of Amazon.
The company’s charge was to be the Earth’s most client- centric company, where guests could find anything they wanted to buy online at the smallest possible prices. Over time, Amazon’s core product has evolved into convenience, with a focus on fast delivery through its network of distribution centers.
Amazon’s deals reached$ 280.52 billion in 2019, making it the top company in Digital Commerce 360’s Top 1000. Still, despite being a retail mammoth, Amazon does n’t make substantial gains from its retail operations due to its strategy of contending on price and convenience. Rather, Amazon relies heavily on its profitable Amazon Web Services( AWS), along with advertising and third- party dealer gains.
Graphical Representation of Amazon’s Sales by Segment (2018–2019)
The table below outlines Amazon’s deals by member for 2018 – 2019, which includes online stores, physical stores, third- party dealer services, subscription services, and AWS.
| Segment | Sales ($ Billion) |
| Online stores | 53.01% |
| Physical stores | 6.45% |
| Third-party seller services | 20.18% |
| Subscription services | 7.21% |
| AWS | 13.15% |
Stock Analysis of Amazon: April 2019–April 2020
Several scatterplots and histograms were created to dissect Amazon’s stock data from April 2019 to April 2020. These visual representations stressed Amazon’s smallest and loftiest stock prices over time, acclimated daily closing stock prices, and trading volume. The analysis handed sapience into Amazon’s stock performance over the time.
A scatterplot of Amazon’s smallest stock prices over time was created by conniving the date on theX-axis and the stock prices on the Y- axis. A scatterplot of Amazon’s loftiest stock prices followed an analogous process, using the loftiest stock price as the Y- axis data points. A histogram was used to fantasize the acclimated daily closing stock prices. This map displayed the frequency of stock prices within certain price ranges. Another histogram anatomized Amazon’s stock trading volume, revealing the frequency of stock trades within specific volume ranges.
Descriptive Statistics of Amazon’s Stock
To give farther perceptivity, the mean, standard, mode, and standard divagation of Amazon’s acclimated daily closing stock prices and diurnal stock traded volume were calculated
- The mean acclimated ending stock price was$ 1,879.70.
- The standard was calculated at$ 1,854.28.
- The mode for the acclimated ending stock price was$ 1,855.32.
- The standard divagation, a measure of stock price volatility, was$ 141.98. Also, descriptive statistics were calculated for Amazon’s diurnal stock traded volume
- The mean diurnal stock traded volume was.
- The median value was$ 1,854.28.
- The mode for stock traded volume was$ 1,855.32.
- The standard divagation for traded volume was$ 141.98.
Conclusion
Amazon’s growth over the times reflects its dominance in both e-commerce and pall services. Its focus on client convenience and invention has helped it become a leader in multiple sectors.
MBA FPX 5008 Assessment 2 Using Analytic Techniques to Add Meaning to Data
Seim, K. (2018). How Amazon…Amazon.com Inc. (2019). Amazon Annual Reports, Proxies and Shareholder letters. Retrieved from https://ir.aboutamazon.com/annual-reports-proxies-and-shareholder-letters/default.aspx
References (APA 7 Format)
- Amazon.com Inc. (2019). Annual reports, proxies, and shareholder letters. https://ir.aboutamazon.com/annual-reports-proxies-and-shareholder-letters/default.aspx
- Schneider, L. (2019). Overview of Amazon.com’s history and workplace culture. The Balance Careers. https://ir.aboutamazon.com/annual-reports-proxies-and-shareholder-letters/default.aspx
- Seim, K. (2018). How Amazon dominates e-commerce.
Rubric Breakdown
| Criteria | Proficient (Pass) | Distinguished (High Pass) |
| Statistical Application | Accurately defines and calculates mean, median, mode, and standard deviation. | Interprets what the specific values (e.g., standard deviation) mean for investor risk and stock volatility. |
| Data Visualization | Correctly identifies the purpose of scatterplots and histograms for the Amazon dataset. | Explains why specific charts (e.g., histograms) are superior for showing price frequency vs. time-series data. |
| Segment Analysis | Breaks down Amazon’s revenue by segment (AWS, Retail, etc.) using the provided percentages. | Evaluates the strategic importance of AWS profit margins compared to high-volume retail sales. |
| Data Meaning | Translates raw numbers into a narrative about Amazon’s market dominance. | Synthesizes descriptive statistics and visual trends to predict future market behavior or risks. |
| Academic Integrity | Information is organized with appropriate headers and basic APA citations. | Professional formatting is flawless; terminology is precise and corrected from initial “scan” errors. |
Step-by-Step Guide
- Collect Data – Gather Amazon’s deals by member, stock prices, and trading volumes from dependable sources.
- Organize Data – produce tables, scatterplots, and histograms to visually represent deals distribution, stock highs and lows, and trading frequency.
- Calculate Descriptive Statistics – cipher mean, standard, mode, and standard divagation for stock prices and trading volumes to measure central tendency and variability.
- dissect Patterns – Identify trends in deals( e.g., AWS donation), stock performance over time, and trading volumes to assess company growth and request geste
- Draw Conclusions – epitomize findings to understand Amazon’s competitive strengths, dominance ine-commerce and pall services, and overall request position.
Frequently Asked Questions
Q1 What’s the main focus of this assessment?
Using logical ways to interpret Amazon’s deals and stock data for meaningful business perceptivity.
Q2 Which deals contributed most to Amazon’s profit?
Online stores, with 53.01 of total deals in 2018 – 2019.
Q3 How was Amazon’s stock anatomized?
Using scatterplots for smallest/ loftiest stock prices, histograms for acclimated daily closing prices and traded volume, and descriptive statistics.
Q4 What descriptive statistics were calculated?
Mean, standard, mode, and standard divagation for stock prices and trading volumes.
Q5 Why are logical ways important for business?
They help interpret data, identify trends, and make informed opinions grounded on evidence.
Integrity Note
Note: Only use this assessment example for learning and structure purpose. Do not submit as your own work.
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