STATISTICS

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!