DQ1: Applying Statistical Thinking to Understand Past History and Possibly Predict

Scenario: Interpret the charts (link below) showing the history of # IPOs from 1975 to 2008: What additional perspective is gained by presenting these data as behavior charts? What action could be taken in terms of Deming’s insistence on using data for “prediction” and why? Week4_DQ 1_charts.doc ["Inherited" from past instructor -- doesn't mean it's right...] Helpful clarifying information: · An initial public offering, or IPO, is the first sale of stock by a company to the public. A company can raise money by issuing either debt or equity. If the company has never issued equity to the public, it's known as an IPO. · As such the number of IPOs can be used as one indicator of the degree of business expansion in a given time period. For your dialogue, ponder: Do you see "patterns" in the time periods corresponding to economic events during these years? Are they the types of things that could happen again? – if so, can you “predict” consequences? Bottom line: Don't concentrate on individual points or individual special cause tests, but, rather, keep the focus when possible on the process "needle." Just because a special cause test is triggered doesn't necessarily mean that the special cause happened there!