Using Business Drivers and Analysis of Effectiveness: Correlations

Correlation: positive, negative, minimal?

Number of indoor basketball leagues in demographic area

High demographic of younger target market.

Three college basketball teams and one NBA team in region to spark interest.

Positive

Lack of any indoor sporting facilities. Negative

Extremely warm geographic area. Minimal Rural geographic setting. High-income geographic area. Positive

High number of indoor sporting facilities.

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The first category of variables has a positive correlation. The relationship is between the number of indoor basketball leagues and the basketball team in the geographic area. The positive correlation is that since the number of indoor leagues increases, the number of groups will also increase. The more the teams play, the more groups they attract to the basketball league. For the second category, many youths in the demographic area will draw more sporting activities. Thus, the correlation between the variables will be negative. The third category of variables has minimal correlation since there is no significant relationship between them. A high number of indoor sporting facilities have no meaningful relationship with the extreme warm geographic area. Thus, the correlation between them tends to be zero. In the fourth category, the sporting activities' rural geographic setting will ensure minimum hiring coaches' costs and that the low-income earner funs incur to watch the games. As a result, more players and teams will join the league; hence, the area will be associated with high income.

What It Means If the Correlation Of 2 Variables Is Positive, Negative, Or Minimal (Close To 0)

When two variables change in a similar direction such that when one variable increases, the other also increases, and when it decreases, the other also decreases. Thus, there is a positive correlation between the two. For example, taller individuals tend to be heavier than shorter individuals—height and weight have a positive correlation. In contrast, negative correlation refers to when two variables correlate so that when one increases, the other decreases, and when it decreases, the further increases. An example is a correlation between altitude and temperature in the troposphere; an increase in height results in to drop in temperature. Minimal correlation represents no relationship between two variables, or when their correlation coefficient lies between -0.1 and 0.1. An example of minimal correlation is between the amount of food one takes and the level of intelligence.

What Do You Deduce from The Correlations? Explain If You Believe These to Be Short or Long-Term Objectives and Outcomes?

From the correlations, I deduce that a firm can utilize the outcome of its variables' correlation to set short-term objectives. For instance, according to Picardo (2019), a negative correlation between variables allows a company to create diversified portfolios that can withstand market volatility and smooth out portfolio returns over the long term. Thus, Big D Inc. can utilize the correlations as short-term objectives and outcomes since most of the results are positive and are bound to change with change in a variable. Besides, the first two correlations indicate that once many indoor basketball leagues play in a high demographic of youth, the probability of attracting more college and NBA teams will be higher.

What Are the Implications for Big D Incorporated Regarding Its Client in The Outdoor Sporting Goods?

The demographics do not favor the business activities of Big D Inc. involving sporting goods. The warm geographic area is also not likely to favor indoor activities.

What Are the Implications for The Penetration into The Indoor Sporting Goods Market?

Penetration into the indoor sporting goods market will boost the business operations of Big D Inc. since there will be market expansion. Market penetration involves strategic steps to increase the number of potential customers (Kenton, 2020). Thus, Big D Inc. will find more consumers for sporting goods.

Also, How Can You Use the Correlation Tools to Identify the Variables in The Research Toward the Expansion into The Indoor Sporting Goods Market?

To identify the research variables that will help expand Big D Inc.’s operations into the indoor sporting goods market, we will determine the correlation coefficients between the variables.

Nickolas (2020) states that a firm can use the correlation coefficient between two variables to determine the degree of their movements' relationship. Utilizing Pearson's correlation coefficient will help Big D Inc. inefficient determination of the variables.