This week, the two DQs are in the form of actual scenarios.
I want to see you work together as a class via your dialogue to analyze these two situations. The bottom line this week: HELP EACH OTHER LEARN and ACT AS A TEAM.
• There are no “right” answers to either question. Analyze and keep asking deeper questions as the week goes on — and, if the data allows, look at the data in different ways as suggested by the classmate questions and attach it as part of the post.
DQ1 Scenario: Interpret the charts 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 [“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!
Individuals Chart: Process Behavior– Number of IPO’s from 1975 to 2008
Moving Range Chart: Number of IPO’s from 1975 to 2008
This week, the two DQs are in the form of actual scenarios.
I want to see you
work together as a class via your dialogue
to analyze these two situations. The bottom line this week: HELP EACH OTHER LEARN and ACT AS A TEAM.
· There are no “right” answers to either question. Analyze and keep asking deeper questions as the week goes on — and, if the data allows, look at the data in different ways as suggested by the classmate questions and attach it as part of the post.
DQ1 Scenario: Interpret the charts 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
[“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!
