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1 Decoding Market Trends: Using Correlations for Sporting Goods Expansion Kaylie Cole Decoding Market Trends: Using Correlations for Sporting Goods Expansion Colorado Technical University 17 December 2023

2 Decoding Market Trends: Using Correlations for Sporting Goods Expansion Introduction Understanding correlations among variables can help better understand the challenges Big D Incorporated is being faced with at this time. By analyzing multiple variables, the definition of correlations, and individual insights and tools, results will be telling to make more informed decisions for the business, Big D Incorporated. Variables: Table Variable A Variable B Correlation: positive, negative, minimal? # of indoor basketball leagues in demographic area # of college and NBA basketball teams positive Three college basketball teams and one NBA team in the region to spark interest. # of indoor sporting facilities negative High demographic of younger target market. Coefficient (Rs) - Avg. Temp. in F of geographic area Minimal (near zero correlation) Lack of any indoor sporting facilities. Coefficient (Rs) - Median Income negative High number of indoor sporting facilities. Avg. Temp. in F of geographic area Minimal (near zero correlation) Extremely warm geographic Median Income Minimal (near zero correlation)

3 Decoding Market Trends: Using Correlations for Sporting Goods Expansion area. Rural geographic setting. Rank of Rural or not Minimal (near zero correlation) High-income geographic area. Rank of median income Positive Interpretation of Correlations Example one states the number of indoor basketball leagues versus the number of the college/NBA basketball teams, this is a positive correlation. A positive correlation of 0.9125178 suggests that areas with more indoor basketball leagues tend to attract a higher number of college and NBA teams. For example, if zone one has five indoor basketball leagues, it might also have a higher number of college and NBA teams. Example two states, three college basketball teams and one NBA team in the region to spark interest versus number of indoor sporting facilities, this would correspond to a negative correlation. The negative correlation of -0.82244 implies that regions with efforts to spark interest in college and NBA teams might have fewer indoor sporting facilities. For example, zone two, with three college basketball teams and one NBA team, may have fewer indoor sporting facilities. Example three states, high demographic of younger target market versus average temperature in Fahrenheit of geographic area, this results in minimal correlation, or close to zero correlation. The minimal correlation (near zero) suggests that the age demographic is not strongly influenced by the average temperature in the geographic area. For example, zone three, with a high number of people under 35, may have varying temperatures without a clear correlation.

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4 Decoding Market Trends: Using Correlations for Sporting Goods Expansion Example four states lack of any indoor sporting facilities versus median income, which results in a negative correlation. The negative correlation indicates that regions with no indoor sporting facilities tend to have lower median incomes. For example, zone four, lacking indoor sporting facilities, may also have lower median incomes. Example five states high number of indoor sporting facilities versus average temperature in Fahrenheit of the geographic area, resulting in minimal, or close to zero correlation. The minimal correlation implies that the number of indoor sporting facilities is not significantly affected by the average temperature. For example, Zone five, with a high number of sporting facilities, may have varying temperatures. Example six states extremely warm geographic area versus median income. There is minimal correlation, indicating that an extremely warm climate does not strongly relate to median income. For example, zone six, with an extremely warm climate, may have varying median incomes. Example seven states rural geographic setting versus rank of rural or not, resulting in minimal or close to zero correlation. The minimal correlation suggests that being in a rural setting does not strongly correlate with the rank of rural areas. For example, zone seven, being rural, may have different rankings regarding rural attributes. Example eight states high-income geographic area versus rank of median income, these result in a positive correlation. The positive correlation suggests that areas with higher incomes tend to have higher ranks in terms of median income. For example, zone eight, with a high income, may have a higher rank in median income. Understanding Correlations

5 Decoding Market Trends: Using Correlations for Sporting Goods Expansion Positive correlation means when one thing goes up, the other tends to go up too. For example, if you exercise more, your overall fitness might also improve. Negative correlation is when one thing goes up, the other tends to go down. Like, if you spend more time watching TV, your physical fitness might decrease. Minimal correlation, close to zero, means there is not much of a connection between two things. An example could be the link between the brand of headphones you have and your preference for a type of coffee – they are not strongly related. Key Deductions and implications from Correlations The correlation results highlight several key deductions with implications for Big D Incorporated in the outdoor sporting goods sector. Firstly, the positive correlation between the number of indoor basketball leagues and the presence of college/NBA teams suggests a potential strategy for enhancing brand visibility. Supporting or establishing more indoor leagues could attract a higher number of college and NBA teams, leading to increased interest in outdoor sporting goods. This could be a viable long-term objective, fostering a sustained connection with sports enthusiasts in areas with active indoor basketball leagues. Conversely, the negative correlation between efforts to spark interest in college/NBA teams and the number of indoor sporting facilities indicates a potential challenge. Regions focusing on team-related initiatives may have fewer indoor facilities, posing a consideration for Big D Incorporated's short-term objectives. To successfully penetrate the indoor sporting goods market, a comprehensive approach beyond team presence could be necessary. The minimal correlation between the high demographic of a younger target market and the average temperature suggests a stable demand for outdoor sporting goods regardless of temperature variations. This insight supports a strategic long-term objective for Big D Incorporated to consistently market to a younger audience.

6 Decoding Market Trends: Using Correlations for Sporting Goods Expansion Correlation Tools and Insights In the context of indoor sporting goods, the correlation tools offer valuable insights. For instance, the negative correlation between the lack of indoor facilities and median income implies that regions without indoor sporting facilities tend to have lower median incomes. To identify variables for research toward expansion into the indoor sporting goods market, Big D Incorporated can leverage this correlation. By focusing on areas with both indoor facilities and higher median incomes, the company can tailor its products and marketing strategies for optimal results in this market segment. Conclusion Overall, understanding these correlations enables Big D Incorporated to make informed decisions, balancing short-term objectives with long-term strategies, and tailoring their approach based on the unique dynamics of the outdoor and indoor sporting goods markets.

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7 Decoding Market Trends: Using Correlations for Sporting Goods Expansion References Correlation . Corporate Finance Institute. (2023, November 21). https://corporatefinanceinstitute.com/resources/data-science/correlation/#:~:text=Using %20a%20scatterplot%2C%20we%20can,of%20the%20relationship%20between %20variables Correlation . JMP. (n.d.). https://www.jmp.com/en_us/statistics-knowledge-portal/what-is- correlation.html#:~:text=Correlation%20is%20a%20statistical%20measure,statement %20about%20cause%20and%20effect Hayes, A. (n.d.). Correlation: What It Means in Finance and the Formula for Calculating It . Investopedia. https://www.investopedia.com/terms/c/correlation.asp Mirabile, H. (2023, December 12). Unit 5 - Live Chat - Week 5-Business Drivers and An. Retrieved from Colorado Technical University, Virtual Campus: https://campus.ctuonline.edu Nickolas, S. (n.d.). Correlation Coefficients: Positive, Negative, and Zero . Investopedia. https://www.investopedia.com/ask/answers/032515/what-does-it-mean-if-correlation-coefficient- positive-negative-or-zero.asp#:~:text=For%20example%2C%20when%20two %20stocks,linear%20relationship%20between%20the%20variables

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