Correlation vs$.$ Causation

Assume that you are a cost accountant working with a plant that manufacturers machinery components. You have noticed that quality costs $($including inspection costs and costs of reworking rejected parts$)$ have increased over the last year. Overhead costs for the plant are allocated using a single overhead cost pool and a single cost driver. In order to better understand the increase in quality costs, you first identified a pool of quality costs over the past year ranging from approximately $$17,200$ to $$24,600.$ You prepared the following data visualization showing the relationship between units of products produced and quality costs.

Explain whether or not quality costs correlate with units produced.

Overhead costs Answer $1$correlate fullycorrelate generallycorrelate inverselycorrelate slightlydo not correlate with the number of units produced$--$as units produced goes Answer $2$updown$,$ cost of quality appears to go Answer $3$updown$.$ The correlation appears to be Answer $4$strongweak as the points Answer $5$mostly fall above a "line."mostly fall below a "line."are clustered on a "line."are not clustered on a "line."

b$.$ Explain the factors you would consider in determining whether or not, units produced cause quality costs.

$1.$ Is it reasonable to assume that as units fluctuate in the future, quality costs will fluctuate Answer $6$insignificantly$?$inversely?proportionately?

$2.$ Does it make sense logically that just because more units are produced, quality costs should Answer $7$increase$?$decrease?stay the same?

$3.$ Is there another factor Answer $8$affecting costs of quality $?$affecting the number of units produced?

c$.$ After discussions with production workers on the factory floor, you determine that the number of line setups may impact the number of rejected parts $($the more setups, the more rejects$).$

$1.$ How might this information affect additional data visualizations that you develop?

Indicate whether the data visualization described below would be helpful $($yes or no$?).$

Answer $9$yesno Number of line setups and quality costs

Answer $10$yesno Number of rejected parts and quality costs

$2.$ How might this affect your understanding of correlation and causation of quality costs?

Provided that the new variables show Answer $11$correlation $/$ causation, there would be a better case to prove Answer $12$correlation $/$ causation between quality costs and a cost driver based on information learned on the factory floor.