minimal?Number of indoor basketball leagues in the demographic area
| Variable A | Variable B | Correlation: |
| positive, negative, minimal? | ||
| Number of indoor basketball leagues in the demographic area | Three college basketball teams and one NBA team in the region to spark interest. | positive |
| High demographic of a younger target market. | Lack of any indoor sporting facilities. | minimal |
| A high number of indoor sporting facilities. | Extremely warm geographic area. | positive |
| Rural geographic setting. | High-income geographic area. | negative |
| Variable A | Variable B | Correlation; negative, positive and little correlation(minimal) |
| Passing in mathematic | Practice | positive |
| science | Mathematics | positive |
| beliefs | Facts | negative |
| English | French | minimal |
The practice of mathematics is positively correlated with passing. an increase in practice leads to increase passing. There is a positive relationship between science and mathematics. Most of science is in calculations and so they need mathematics. There are mathematical calculations in science subjects like physics. Beliefs and facts were found to have negative correlations. One is quite opposite of the other in that facts lead to no beliefs and an increase of beliefs lead to a decrease in facts. English and French languages are different; however, there might be a small or minima relationship between the two. The value of the correlation lies between +1 and -1. Any value between zero and either positive or negative correlation is the minimal correlation. Zero value or any amount close to it indicates no relationship between the coefficients. If the correlation of two variables is found to be positive, it means that one variable increases when the other increase. The value of r is always +1 implying a strong relationship between the two variables. For example, there is a positive correlation between the increase in several customers with good customer satisfaction. A high number of clients is related to the high increase in customer’s satisfaction.
Negative correlations occur where an increase in one variable lead to decrease in the other. The value of negative correlation which measures it indicates the strongest negative relationship. Any number close to -1 shows a strong correlation of the data in a negative way. Take for instance a region with hunters and antelopes. The high numbers of hunters have a relationship with a reduction in the population of antelopes in the region. Increase in hunters results in a decrease in the number of antelopes. The last correlation is minimal which is depended on the closeness of a variable to zero. It occurs where both negative and positive correlations do not take effect. For example relationship between French and English language is moderate or has a moderate correlation.
It is found that correlations do not show causal relationships between two different variables. For example, it cannot be said that the decrease in population of animals is caused by humans even though there is a correlation between the two. If there might be causation, then its coefficients cannot tell which variable is the effect and cause. Zero coefficient does not necessarily imply no relationship but it might be a non-linear relationship. I believe this analysis is a long-term outcome because it cannot change in future. The implications of big D incorporated regarding customers in outdoor sporting goods are the expansion of alternative sales channels. Majority of outdoor sporting goods are related to instructions. For example, martial arts uniform is sold more in instruction related groups or teams. Implications for penetration into the indoor sporting goods market is a negative and positive correlation. Correlation tools can be used in indoor sporting goods market to show strengths and weaknesses towards the expansion of the market