Use and Misuse of Statistics

From an article at Knowledge @ Wharton

“Today, consumers of information are drowning in data,” says Justin Wolfers, Wharton professor of business and public policy. “Terabytes of data are being generated from the constant measurement of businesses, workers, government and other activity, and there are many ways to draw inferences from the raw data. Unfortunately, many of them lead in the wrong direction.”

For example, he says a chain of retail stores may analyze its operations for a set period and find that those times when it reduced its sales prices coincided with times that overall sales fell. “That could lead the chain to conclude that low prices spurred a reduction in sales volume,” says Wolfers. “But the true causal link may be deeper than that. Before the retailer raises prices in an attempt to increase sales, it should examine additional issues to see if overall demand during the period was influenced by other factors. For example, perhaps the firm historically runs its semi-annual sales during slow sales periods. If this is the case, low sales are causing price declines, rather than price declines lowering sales.”