Business analytics techniques facilitate decision making by transforming large amounts of raw data into meaningful information. Many businesses rely on analysis of relevant historical data to make key strategic and operational decisions. In business analytics, you often need to draw conclusions about a population of interest, but gathering data on the entire population may not be feasible. In these cases, data are gathered from a sample or subset of the population, and analyses done on the sample are used to draw inferences regarding the overall populationa process referred to as inferential statistics. The smaller group (the sample) provides measurements (the statistic) that serve as estimates for the larger group (the population) and its true measurement (the parameter). Rather than restricting estimates to single numbers that would be exactly correct or incorrect, analysts calculate confidence intervalsranges of possible values within which there can be a certain percent confidence that the true population parameter falls. Creating meaningful information from raw data involves two essential steps: first, representing data effectively in graphical format and calculating required statistics; second, interpreting those graphics and statistics to apply them in the business context. In this assessment, you will sharpen your analytics skills by downloading real-life stock data, creating graphical representations (scatterplots and histograms), calculating descriptive statistics (mean, median, mode, standard deviation), and connecting these interpretations explicitly to business implications. The statistical techniques covered in this course are parametric techniques, which require certain assumptions about underlying distributions for results to be reliable. Nonparametric techniques, which require no assumptions about underlying distributions, are often used when parametric assumptions are not met, though these are beyond the scope of this introductory course. Overview Business analytics techniques facilitate decision-making by transforming large amounts of raw data into meaningful information and interpretations. Many businesses rely on analysis of relevant historical data to make key strategic and operational decisions with the goal of gaining or maintaining competitive advantage. Understanding how to use techniques such as graphical representation and descriptive statistics to translate raw data into useful information is a valuable skill set in the business environment. In this assessment, you will sharpen your analytics skills by analyzing 10 years of stock data from a publicly traded company, creating an informative business report with professional graphics, and interpreting descriptive statistics. Your interpretation efforts will explicitly connect graphics and statistics to practical business implications in the conclusion, where you will present supported recommendations. All conclusions must be evidence-based and supported with citations; opinion is not allowed. Scenario/Your Role You are a business analyst evaluating a publicly traded company that your organization is considering for acquisition or partnership. Your supervisor has tasked you with conducting a comprehensive 10-year stock performance analysis, including comparison against key competitors, to inform this strategic decision. You will analyze historical stock data using descriptive statistics and professional data visualizations, then synthesize your findings with market analyst commentary to develop an evidence-based investment recommendation. Your business report will be presented at a company-wide leadership meeting where executives will use your analysis to make final decisions about pursuing this opportunity. Instructions Choose a publicly traded company for your organization to invest in. Begin by doing some research on companies that interest you and have been in the news recently for something positive. Choose a company that meets the following criteria: It has been in the news within the last 610 months for something positive (that is, an innovation, a new product, customer service, stock values, et cetera). It plays in only one business platform. Do not pick Apple, Amazon, Disney, Tesla, or other companies that work in multiple industries; that will make your competitor analysis too challenging. Choose a company that does all of its business in a single industry. Also identify: At least two direct competitors in the same single industry Confirm all companies (your chosen company + competitors) have 10 years of publicly available stock data Once you have chosen a company to invest in, develop a detailed, well-supported report (at least eight pages), outlined as follows: Report Structure and Requirements (810 Pages) Your comprehensive business analytics report must include the following sections: Section 1: Business Context and Introduction (1.52 pages) Note: You can find the information via the Capella library. For example, Hoovers Company Profiles and Industry Publications. See the Capella librarys MBA Program Guide Data page for help building a search. Provide comprehensive context for your analysis: Company Overview: Company history, mission, and values. Core products and business platform. Geographic reach and market presence. Industry position and competitive landscape. Current Relevance: Explain why this company has been in the news recently (within the last 610 months). Describe the positive development/innovation that drew attention. Connect this news to the company’s strategic direction. Competitor Comparison Table: Using the most recent year of available data, create a professional table including the following metrics for your company and at least two competitors: Market share. Total sales. Number of employees. Total assets. Section 2: Stock Data Collection and Analysis (34 pages) Step 1: Collect Stock Data Access historical stock data from Macrotrends.com, Nasdaq.com, Yahoo Finance, or similar reputable financial data sources. Download Parameters: Time Period: Last 10 years from today. Frequency: Daily. Required data columns: Date, Open, High, Low, Close, Volume. Important: Save your Excel file – you will use it for all graphics and statistics. Step 2: Create Required Graphics (Five Graphics Total) Create the following five graphics with professional formatting: Graphic 1: High Stock Price Scatter Plot. X-axis: Date (labeled clearly with appropriate date format). Y-axis: Highest Daily Stock Price in USD. Include: 60-day moving average line (use distinct color). Trend line (use distinct color different from moving average). Legend identifying each line type (data points, moving average, trend line). Title: “[Company Name] Highest Daily Stock Price with 60-Day Moving Average (YYYYYYYY).” Interpretation Paragraph Required Write at least one well-supported paragraph addressing: What does this graphic represent? What does the shape tell you about price movement over time? What trends, patterns, or significant events are visible? What does the moving average reveal about overall direction vs. daily volatility? What does the trend line indicate about long-term trajectory? Graphic 2: Low Stock Price Scatter Plot. Same specifications as Graphic 1, but tracking lowest daily stock price. Include 60-day moving average, trend line, and legend. Interpretation Paragraph Required Address the same analytical questions as Graphic 1. Graphic 3: Competitor Comparison Scatter Plot. X-axis: Date. Y-axis: Stock Price in USD. Plot: Your company + at least 2 competitors (each in different color). Include: Legend identifying each company. Title: “Stock Price Comparison: [Your Company] vs. Competitors (YYYYYYYY).” Interpretation Paragraph Required Write at least one well-supported paragraph addressing: How does your company’s stock performance compare to competitors over 10 years? Which company has been most/least volatile? Are there periods where performance diverges? What might explain this? What competitive advantages or disadvantages does this suggest? Graphic 4: Closing Price Histogram. X-axis: Price ranges (adjust bin size for meaningful distribution shape). Y-axis: Frequency. Include: Legend. Title: [Company Name] Closing Price Distribution (YYYYYYYY). Interpretation Paragraph Required Write at least one well-supported paragraph addressing: What does the shape of the distribution tell you? Is the data normally distributed, skewed, bimodal? What price ranges are most common? What does this tell you about the stock’s typical trading range? Graphic 5: Trading Volume Histogram. X-axis: Volume ranges (adjust bin size for meaningful distribution shape). Y-axis: Frequency. Include: Legend. Title: “[Company Name] Trading Volume Distribution (YYYYYYYY).” Interpretation Paragraph Required Address: What does the shape tell you about typical trading activity? Are there outliers suggesting unusual trading days? What does volume distribution tell you about liquidity and investor interest? Section 3: Descriptive Statistics and Interpretation (22.5 pages) Use Excel’s Descriptive Statistics function to create two comprehensive tables: Table 1: Daily Closing Price Statistics (10 years). Calculate: Mean. Median. Mode. Standard Deviation. Variance. Range. Minimum. Maximum. Count. Table 2: Daily Trading Volume Statistics (10 years). Calculate: Mean. Median. Mode. Standard Deviation. Variance. Range. Minimum. Maximum. Count. Interpretation Requirements for Statistics. For the first five statistics in EACH table, provide several well-supported sentences explaining: Explains what each statistic means (mean, median, mode, SD, variance). Then for each table, provides 23 paragraphs on what the SPECIFIC VALUES tell you about THIS company. Focuses on business interpretation, not statistical definitions. Section 4: Conclusions and Recommendations (1.52 pages) Your conclusion (1.52 pages) should synthesize findings into a cohesive narrative that: Opens with 35 key findings from your analysis. Connects these findings to strategic implications. Integrates analyst perspectives to validate or challenge your findings. Concludes with a clear recommendation (invest/partner/avoid) supported by specific evidence. Acknowledges limitations and suggests future research. Your conclusion should read as a cohesive executive summary. Additional Requirements Your assessment should also meet the following requirements: Format: Use the MBA Academic and Professional Document Guidelines [PDF] to prepare a professional report of at 810 (single-spaced) pages. Written communication: Ensure your written communication is free of errors that detract from the overall message. References: Provide an APA-formatted references page (remember to cite the source of your financial data, analyst comments and support for your interpretations). Use a minimum of six sources, though typically such a report would have at least 10 sources.