MBA FPX 5008 Assessment 3 Applying Analytic Techniques to Business

Name

Capella University

MBA-FPX 5008 Applied Business Analytics

Prof. Name

Date

Starbucks Corporation: Applying Analytical Techniques to Business

Starbucks Corporation’s historical stock performance can be evaluated using descriptive statistics, histograms, scatterplots, and market analysis to understand price movements, trading activity, and potential business risks. In this analysis, historical data from September 17, 2018, to September 13, 2019, is used to examine Starbucks’ adjusted closing prices, daily trading volume, and stock price trends. The findings suggest that Starbucks experienced an overall upward stock price trend during the period, although fluctuations in trading volume, international market conditions, and industry risks created uncertainty. These analytical techniques help explain historical market behavior and show how data can support business planning, investment analysis, and strategic decision-making.

Starbucks Corporation and Its Business Strategy

Starbucks is a global specialty coffee company known for its beverages, customer experience, and internationally recognized brand. Its business model combines company-operated stores with licensed locations and international partnerships. This structure allows the company to maintain direct control over many customer experiences while expanding into markets through different operating arrangements.

During the period discussed in this analysis, Starbucks continued to pursue international expansion and diversify its product offerings. Its portfolio included beverages, packaged products, and brands associated with tea and fresh juice. Such initiatives provided opportunities to reach additional customer segments and reduce dependence on a single product category.

MBA FPX 5008 Assessment 3 Applying Analytic Techniques to Business

Historical industry reports also highlighted the growing importance of specialty coffee in the United States. Brown (2019) discussed trends in coffee and beverage consumption, while Menke (2018) examined developments in the specialty coffee industry. These market conditions created opportunities for Starbucks to strengthen its position through product innovation, customer loyalty, and strategic expansion.

International growth was another important component of Starbucks’ business strategy. The United States remained a major market, while China offered significant growth potential. However, international expansion also introduced risks related to local consumer preferences, competition, trade relationships, and economic conditions. Analyzing the company’s historical stock performance alongside these business factors helps provide a broader understanding of its market position.

Graphical Representation of Starbucks Stock Data

Graphical analysis makes large datasets easier to interpret by showing distributions, patterns, and relationships between variables. Histograms help explain how frequently stock prices or trading volumes fall within particular ranges, while scatterplots reveal how stock prices change over time.

The following analysis examines historical Starbucks stock data covering September 17, 2018, through September 13, 2019. Because the dataset reflects a specific historical period, the findings should not be interpreted as a description of Starbucks’ current stock performance or as a forecast of future returns.

Interpreting the Histogram of Daily Trading Volume

Figure 1. Histogram of Starbucks daily trading volume (Yahoo Finance, 2019)

Figure 1 illustrates the distribution of Starbucks shares traded each day during the selected period. The horizontal axis represents ranges of daily trading volume, while the vertical axis shows the frequency of observations within each range.

Most observations fall within the lower-to-middle trading-volume ranges, approximately 7.1 million to 14.3 million shares. A smaller number of observations appear at higher volumes, creating a longer right tail. This pattern is consistent with a right-skewed distribution, particularly when the mean exceeds the median.

The mean daily trading volume was approximately 10,030,024 shares, compared with a median of 9,223,100 shares. The difference suggests that some unusually high-volume trading days increased the average. Such observations may occur around earnings announcements, major corporate developments, broader market movements, or changes in investor expectations.

Trading volume measures market activity rather than the direction of price movements. High volume can accompany either rising or falling prices, so it should be interpreted alongside price data and relevant market events. The distribution indicates that Starbucks experienced variation in daily trading activity, but volume alone cannot establish whether investors were optimistic or pessimistic.

Interpreting the Histogram of Adjusted Closing Prices

Figure 2. Histogram of Starbucks adjusted closing stock prices (Yahoo Finance, 2019)

Figure 2 shows the distribution of Starbucks’ daily adjusted closing stock prices. The horizontal axis represents adjusted closing price ranges, and the vertical axis indicates how often prices occurred within those ranges.

The reported mean adjusted closing price was $73.72, while the median was $70.88. Because the mean is greater than the median, the distribution may be positively skewed, with relatively high prices pulling the average upward. However, the precise shape of a distribution should be confirmed by examining the complete dataset and the histogram itself.

The mean represents the arithmetic average of the observed prices, whereas the median identifies the middle observation after the values are arranged in order. Comparing these measures helps analysts understand whether unusually high or low observations may influence the average.

Adjusted closing prices are useful for historical analysis because they account for certain corporate actions, such as dividends and stock splits, depending on the data provider’s adjustment methodology. They can therefore provide a more meaningful basis for evaluating historical price performance than unadjusted closing prices alone.

The histogram helps summarize the range and distribution of historical prices. However, it does not independently show whether the stock increased or decreased over time. A time-based graph or scatterplot is needed to examine that trend.

Interpreting Starbucks Stock Price Scatterplots

Scatterplots show the relationship between two variables. In a stock price analysis, time can serve as the independent variable on the horizontal axis, while the observed stock price serves as the dependent variable on the vertical axis. These graphs help analysts identify general trends, fluctuations, and potential outliers.

Scatterplot of Starbucks’ Highest Daily Stock Prices

Figure 3. Scatterplot of Starbucks’ highest daily stock prices (Yahoo Finance, 2019)

Figure 3 illustrates the relationship between time and Starbucks’ highest daily stock prices from September 17, 2018, through September 13, 2019. The overall pattern shows a positive relationship, indicating that the highest recorded prices generally increased over the selected period.

The historical market commentary cited by Whitfield (2019) described a strong rally in Starbucks shares during 2019. The upward pattern in the scatterplot is consistent with that historical account, although the graph alone does not explain the reasons for the increase.

Potential influences on stock performance include revenue growth, customer demand, business expansion, earnings announcements, investor expectations, and broader market conditions. These factors should be examined alongside the plotted data before drawing conclusions about the causes of price changes.

A positive relationship between time and price does not mean that the stock increased every day. Daily fluctuations may still occur within a longer-term upward trend. Similarly, a small decline near the end of the observation period does not necessarily indicate a sustained reversal. Additional observations would be required to determine whether the movement continued.

Scatterplot of Starbucks’ Lowest Daily Stock Prices

Figure 4. Scatterplot of Starbucks’ lowest daily stock prices (Yahoo Finance, 2019)

Figure 4 presents the relationship between time and Starbucks’ lowest daily stock prices during the same historical period. Similar to the highest-price scatterplot, the data shows a generally upward pattern.

The similarity between the two graphs suggests that the overall upward movement was not limited to the highest prices recorded each day. The lower end of the daily price range also generally increased, providing additional evidence of positive historical price performance during the period.

However, daily highs and lows represent intraday price extremes rather than the price at which the stock finished trading. These measures can be useful for understanding daily price ranges, but adjusted closing prices are generally more suitable for evaluating historical performance across periods that include dividend adjustments or stock splits.

Taken together, the scatterplots show how graphical analysis can help identify trends that may be less apparent when examining individual daily observations. They also demonstrate why multiple measures should be considered before making conclusions about stock performance.

Descriptive Statistics for Starbucks Stock Prices

Descriptive statistics summarize a dataset through measures such as the mean, median, and standard deviation. These measures help analysts understand the typical observed value, the distribution of data, and the degree of variation around the average.

Mean, Median, and Standard Deviation of Adjusted Closing Prices

The mean adjusted closing stock price for Starbucks was reported as $73.72 during the period from September 17, 2018, to September 13, 2019. The mean is calculated by adding all observed adjusted closing prices and dividing the total by the number of observations.

The median adjusted closing price was $70.88. Unlike the mean, the median is not as strongly influenced by extremely high or low observations. The difference between the two measures suggests that higher prices may have influenced the average, which is consistent with the possibility of a right-skewed distribution.

The reported standard deviation was 12.5. Standard deviation measures how widely observations vary around their mean. A larger standard deviation indicates greater dispersion, while a smaller value indicates that observations tend to cluster more closely around the average.

MBA FPX 5008 Assessment 3 Applying Analytic Techniques to Business

Although the standard deviation provides useful information about price variation, it should not be used alone to classify a stock as low-risk or high-risk. Stock risk can also depend on returns volatility, market conditions, financial performance, valuation, and an investor’s time horizon. In addition, the standard deviation of raw price levels is different from the standard deviation of daily returns, which is commonly used to assess investment volatility.

For this reason, the reported statistics provide a useful historical summary, but a more complete investment analysis would also examine daily percentage returns and compare Starbucks with an appropriate market benchmark.

Mean, Median, and Standard Deviation of Daily Trading Volume

Starbucks’ mean daily trading volume was reported as 10,030,024 shares, while the median was 9,223,100 shares. The mean exceeded the median, suggesting that a limited number of unusually high-volume days increased the average trading volume.

The reported standard deviation of daily trading volume was 4,876,760 shares. This indicates substantial variation in the number of shares traded from one observation to another. Some days experienced much greater trading activity than others.

Changes in trading volume may reflect several factors, including earnings announcements, changes in investor expectations, company news, economic developments, or broader market volatility. However, higher volume does not automatically indicate increased demand for a stock or a positive outlook. Every completed trade involves both a buyer and a seller, and volume must be interpreted alongside price movements and market context.

For Starbucks, the difference between the mean and median suggests that average trading activity was influenced by higher-volume observations. Investors and business analysts could investigate these dates further to determine whether major announcements or broader market events coincided with unusually high trading activity.

Business Implications of Starbucks’ Historical Stock Performance

The combination of graphical analysis and descriptive statistics provides several insights into Starbucks’ historical performance. The scatterplots show a general upward trend in the highest and lowest daily stock prices, while the histograms reveal how prices and trading volumes were distributed. The descriptive statistics further demonstrate that a small number of high observations may have influenced the average price and trading volume.

These findings can support business analysis by encouraging decision-makers to examine market data alongside company fundamentals. Revenue growth, customer demand, operating costs, international expansion, and competitive pressures can all influence investor expectations. However, historical stock movements alone cannot establish whether a company’s strategy caused a particular price change.

International Expansion and Growth Opportunities

International expansion has been an important part of Starbucks’ business strategy. Established markets can provide opportunities to strengthen customer relationships and improve store productivity, while emerging markets may offer additional growth potential.

China was a particularly important market in the historical context of this analysis. However, expansion into international markets also creates challenges related to local competition, consumer preferences, trade relationships, and regulatory requirements. A successful strategy requires Starbucks to balance global brand consistency with local market adaptation.

Investors evaluating international expansion should examine store growth, comparable-store sales, operating margins, customer demand, and the costs associated with entering new markets. These indicators provide more detailed evidence of business performance than stock price movements alone.

Trade Relations and Consumer Sentiment

Trade tensions between the United States and China were identified in contemporary reporting as a potential concern for Starbucks’ Chinese operations (Moon, 2018). Political tensions can influence consumer sentiment, create uncertainty for international businesses, and affect expectations about future growth.

Nevertheless, a decline in a stock price cannot be attributed to a single event without further evidence. To assess whether trade tensions influenced Starbucks’ stock performance during the selected period, analysts would need to compare the timing of relevant announcements with stock returns and consider other market developments occurring at the same time.

This distinction is important because stock prices reflect multiple influences, including company-specific news, investor expectations, interest rates, and overall market movements. A careful analysis avoids treating a plausible explanation as a proven cause.

Coffee Supply, Climate, and Operating Risks

Starbucks depends on a reliable supply of coffee beans and other ingredients to maintain product quality and meet customer demand. Weather conditions, changing climate patterns, crop diseases, transportation disruptions, and shifts in commodity prices can affect supply costs and availability.

These pressures may influence operating margins and create uncertainty about future profitability. The company can manage some of these risks through supplier relationships, responsible sourcing practices, long-term purchasing arrangements, and supply-chain monitoring. However, such measures cannot eliminate all market or environmental risks.

For analysts, the important consideration is how supply-chain developments affect revenue, expenses, margins, and customer experience. Linking these business indicators with historical stock data can provide a more complete picture of the company’s financial performance.

Applying Analytical Techniques to Business Decisions

MBA FPX 5008 Assessment 3: Applying Analytic Techniques to Business

Analytical techniques can help businesses make more informed decisions by turning raw data into useful insights. In Starbucks’ case, stock prices and trading volumes offer one perspective on investor behavior and historical market performance. Similar analytical methods can also be applied to sales, customer preferences, product performance, marketing campaigns, and store expansion decisions.

Adjusted closing prices are particularly useful when reviewing historical stock data because they account for certain corporate actions, depending on the data provider’s methodology. Starbucks has also historically paid dividends to shareholders. Dividends represent a distribution of company value to investors; they should not automatically be described as devaluing the company. When a stock trades ex-dividend, its market price may adjust to reflect the distribution, while adjusted-price series account for dividends according to the provider’s methodology.

MBA FPX 5008 Assessment 3 Applying Analytic Techniques to Business

For business decision-making, Starbucks can use data analysis to evaluate demand, plan store locations, assess product performance, refine promotions, and measure marketing effectiveness. For example, sales data combined with customer demographics and location information may help identify markets where a new store is likely to perform well. Product-level data can also help management evaluate seasonal demand and decide which offerings deserve additional investment.

Historical reporting from 2019 described strong Starbucks revenue performance during that period (Shama, 2019). However, revenue growth and stock price appreciation are different measures. Revenue reflects sales generated by the business, while a stock price reflects market expectations and other factors affecting investor demand. Analysts should consider both alongside profitability, cash flow, operating expenses, and long-term investment needs.

A disciplined approach to business analytics should include checking data quality, selecting appropriate statistical measures, interpreting results in context, and recognizing uncertainty. These practices help prevent misleading conclusions and support better strategic decisions.

Conclusion

The historical analysis of Starbucks Corporation demonstrates how histograms, scatterplots, and descriptive statistics can be used to examine stock prices and trading volume. During the period from September 17, 2018, to September 13, 2019, the stock price data showed a generally upward trend, while the trading-volume statistics indicated variation and the presence of high-volume observations.

The reported mean adjusted closing price of $73.72 exceeded the median of $70.88, suggesting that higher observations influenced the average. Similarly, mean daily trading volume exceeded median volume, indicating that unusually active trading days contributed to the overall distribution. These findings provide a statistical summary of historical market behavior, but they do not independently predict future returns or establish the causes of price movements.

For MBA FPX 5008 Assessment 3, the central lesson is that analytical techniques are most valuable when combined with business context. Starbucks’ international expansion, customer demand, competitive position, supply-chain exposure, and operating performance should be considered alongside stock market data. By using reliable data, selecting appropriate measures, and avoiding unsupported causal claims, business leaders can make more informed decisions about strategy, investment, marketing, and long-term growth.

Frequently Asked Questions

What analytical techniques can be used to evaluate Starbucks stock performance?

Histograms, scatterplots, mean, median, and standard deviation can help summarize historical stock prices and trading volume. Analysts may also examine daily returns, moving averages, and comparisons with market benchmarks to develop a more complete understanding of performance.

What does the mean adjusted closing price tell us about Starbucks stock?

The mean adjusted closing price represents the average adjusted price across the observations in the dataset. In this analysis, the reported mean was $73.72. It provides a summary of the historical price level but does not, by itself, indicate whether the stock is undervalued or likely to rise.

Why was Starbucks’ mean trading volume higher than its median?

The mean trading volume was approximately 10.03 million shares, compared with a median of 9.22 million. This difference suggests that some higher-volume trading days increased the average. Further investigation would be needed to determine what events contributed to those observations.

What does a right-skewed histogram indicate?

A right-skewed histogram has a longer tail toward higher values. When the mean exceeds the median, it can indicate that relatively high observations are pulling the average upward. The exact distribution should still be verified by reviewing the underlying data and graph.

Does an upward stock price trend guarantee future growth?

No. An upward historical trend describes what happened during a specific period; it does not guarantee future performance. Future stock prices may be influenced by company results, investor expectations, competition, economic conditions, and unexpected events.

How can Starbucks use data analytics to improve business decisions?

Starbucks can use data analytics to understand customer preferences, forecast demand, assess product performance, optimize marketing campaigns, evaluate store locations, and monitor operational efficiency. Combining these insights with financial and market data can improve planning and resource allocation.

Why are adjusted closing prices important in stock analysis?

Adjusted closing prices account for certain corporate actions, such as dividends and stock splits, according to the data provider’s methodology. This can make historical comparisons more meaningful than using unadjusted closing prices alone.

References

Brown, N. (2019, March 11). 2019 coffee and beverage trends: Inside the NCA’s annual report. Daily Coffee News. https://dailycoffeenews.com/2019/03/11/2019-coffee-and-beverage-trends-inside-the-ncas-annual-report/

Cuofano, G. (2019). Starbucks business model in a nutshell. FourWeekMBA. https://fourweekmba.com/starbucks-business-model/

Eckstein, J. (2019, September 24). How Starbucks makes money. Investopedia. https://www.investopedia.com/articles/markets/021316/how-starbucks-makes-moneysbux.asp

Ganti, A. (2019, April 23). Stock dividend. Investopedia. https://www.investopedia.com/terms/s/stockdividend.asp

Menke, J. (2018). The state of the specialty coffee industry. Specialty Coffee Association. https://sca.coffee/sca-news/an-insider-look-at-the-state-of-the-specialty-coffee-industry-in-2018

MBA FPX 5008 Assessment 3 Applying Analytic Techniques to Business

Moon, L. (2018, July 26). Trade war threatens Starbucks’ success in China. Business Insider. https://www.businessinsider.com/trade-war-threatens-starbucks-success-in-china-2018-7

Shama, G. (2019, April 25). Starbucks’ Q2 revenue growth tops expectations. MarketWatch. https://www.marketwatch.com/story/starbucks-q2-revenue-growth-tops-expectations-2019-04-25

Yahoo Finance. (2019). Starbucks Corporation (SBUX) historical stock data. https://finance.yahoo.com/quote/SBUX/history/

Whitfield, G. (2019, January 10). Starbucks stock rallies for 2019. Zacks. https://www.zacks.com/stock/news/352051/starbucks-stock-rallies-for-2019