Final answer:
To analyze data and identify patterns, such as determining product purchase affinities in a retail setting, companies use Association rules, a method that detects common patterns or co-occurrences in transactional data.
Step-by-step explanation:
When companies seek to analyze data and identify patterns in consumer purchasing behavior, they often use a technique called Association rules. In the case of a home improvement retailer like Lowe's, to determine the likelihood that customers who buy a garden hose also often purchase a sprinkler, association rules, which are a part of market basket analysis, would be most relevant. This method is built on the premise that certain products are bought together with a higher probability than others. Unlike regression analysis that investigates the relationship between dependent and independent variables, association rules look for simple correlations or patterns of co-occurrence that are much more typical in transactional or purchase data.
Regression analysis could be used as well, especially if we are looking to understand the influence of external factors on sales, but it is not as direct as association rules for discovering purchase combinations. Factor analysis and conjoint analysis are more suited to understanding underlying dimensions or consumer preference structures, and would therefore not be the most effective method for identifying direct associations in purchasing patterns such as the example given.