Statistical Engineering: Principles and Examples
September 20, 2011

Lynne B. Hare, Ph.D. Statistical Strategies, LLC S i i lS i C lynne.hare@comcast.net

Outline
1. Motivation o a o
a. b. c. d. Not enough statisticians Management demand Balance with other staff Other technologies in competition p Background Definition Principles Comments

3 3. Examples a p es
NIST Standard Reference Materials b. Industrial consumer b I d i l complaints [Group Exercise] a. Closed loop dosing systems c. Process Variation c Process Variation Reduction d. Lean Six Sigma
Slide 2

a.

2. Statistical Engineering
a. b. c. d. d

Lynne s Background (Why me?) Lynne’s Background (Why me?)
• 40+ years in industry
– Nabisco, then Kraft , – Unilever (Lipton) – Hunt‐Wesson Foods

• Academic
– AB Math The Colorado AB Math, The Colorado College – MS, Applied and Mathematical Statistics, Rutgers – PhD, Interdisciplinary, Rutgers

• Government: NIST Government: NIST • Academia
– Cal. St. Fullerton (MBAs) – Rutgers (Experiment Station) ( )

• ASA
– Chair P&Q Division – Fellow ‘94

• Consulting
– Consumer goods – Pharmaceuticals – R&D, Manufacturing, Quality

• ASQ
– Chair Statistics Division – Fellow ’86 – Column Quality Progress Column: Quality Progress
Slide 3

Statisticians??

Not sure N t

Yes

No

Don’t care. This is the only session that looked remotely interesting. that looked remotely interesting
4

How can you tell? How can you tell?
• If you have more than one pen with you If you have more than one pen with you • If you know more than one joke about the binomial distribution binomial distribution • If your glasses are thicker than mine • If you are too shy to be an accountant • If you talk to your colleagues in SAS y y g

5

1. Motivation 1 Motivation
Statistical Engineering

1. Motivation
The State of Statistics as