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TUM School of Management Production and Supply Chain Management
Prof Martin Grunow Technische Universitt Mnchen
Quality Engineering & Management
Session 4.2: Descriptive vs. Inferential Statistics
Dr. Holly Ott Production and Supply Chain Management
Chair: Prof. Martin Grunow TUM School of Management
Holly Ott 1 Quality Engineering & Management Module 4
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TUM School of Management Production and Supply Chain Management
Prof Martin Grunow Technische Universitt Mnchen
Learning Objectives
Understand the purpose and importance of descriptive statistics.
Review the concepts of histograms, box-and-whisker plots and
the
most common measurements of location and dispersion.
Explain the purpose of inferential statistics and point
estimates for a population parameter.
Identify unbiased point estimates for the mean and standard
deviation of a normally distributed random variable.
Holly Ott 2 Quality Engineering & Management Module 4
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TUM School of Management Production and Supply Chain Management
Prof Martin Grunow Technische Universitt Mnchen
Descriptive Statistics
Empirical methods to describe populations: arranging and
summarizing data to obtain useful information
Frequency Distribution: Histograms Box-and-Whisker Plots
Measures of Location Measures of Dispersion
Holly Ott 3
2012 from "A First Course in Quality Engineering: Integrating
Statistical and Management Methods of Quality" by K.S.
Krishnamoorthi. Reproduced by permission of Taylor and Francis
Group, LLC, a division of Informa plc.
Quality Engineering & Management Module 4
-
TUM School of Management Production and Supply Chain Management
Prof Martin Grunow Technische Universitt Mnchen
Frequency Distribution - Histogram Fill-weights of
deodorant in cans:
Holly Ott 4 Quality Engineering & Management Module 4
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TUM School of Management Production and Supply Chain Management
Prof Martin Grunow Technische Universitt Mnchen
Histogram - Example A manufacturer of thermostats used in
toasters and ovens was experiencing considerable returns from
customers because the thermostats failed in calibration tests.
The failures were traced to the width of a small key-way, called
the dog-width, on a tiny shaft 3/8 in. in diameter. These key-ways
were typically cut on a milling machine that had two cutting heads
and the cut shafts were collected in a common hopper below the two
cutters.
The uniformity of the dog-widths had to be ensured in order to
prevent calibration failures.
Holly Ott 5
2012 from "A First Course in Quality Engineering: Integrating
Statistical and Management Methods of Quality" by K.S.
Krishnamoorthi. Reproduced by permission of Taylor and Francis
Group, LLC, a division of Informa plc.
Quality Engineering & Management Module 4
-
TUM School of Management Production and Supply Chain Management
Prof Martin Grunow Technische Universitt Mnchen
Histogram - Example A sample of 100 shafts was taken from the
hopper of one of the milling machines and the widths were measured
and plotted in a histogram.
The histogram typifies a bimodal distribution, which is a
frequency distribution with two modes, or two peaks, indicating
that two different distributions are mixed together in this
populationone within the specification, and one almost outside the
specification.
Holly Ott 6
2012 from "A First Course in Quality Engineering: Integrating
Statistical and Management Methods of Quality" by K.S.
Krishnamoorthi. Reproduced by permission of Taylor and Francis
Group, LLC, a division of Informa plc.
Quality Engineering & Management Module 4
-
TUM School of Management Production and Supply Chain Management
Prof Martin Grunow Technische Universitt Mnchen
Cumulative Frequency Distribution
Holly Ott 7
2012 from "A First Course in Quality Engineering: Integrating
Statistical and Management Methods of Quality" by K.S.
Krishnamoorthi. Reproduced by permission of Taylor and Francis
Group, LLC, a division of Informa plc.
Quality Engineering & Management Module 4
-
TUM School of Management Production and Supply Chain Management
Prof Martin Grunow Technische Universitt Mnchen
The box-and-whisker (B&W) plot is another compact way of
representing a population with variability, and it is especially
useful when comparing several distributions with respect to their
central value and dispersion.
Holly Ott 8
2012 from "A First Course in Quality Engineering: Integrating
Statistical and Management Methods of Quality" by K.S.
Krishnamoorthi. Reproduced by permission of Taylor and Francis
Group, LLC, a division of Informa plc.
Quality Engineering & Management Module 4
Box-and-Whisker Plots
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TUM School of Management Production and Supply Chain Management
Prof Martin Grunow Technische Universitt Mnchen
Holly Ott 9 Quality Engineering & Management Module 4
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TUM School of Management Production and Supply Chain Management
Prof Martin Grunow Technische Universitt Mnchen
Measures of Location and Dispersion
Holly Ott 10 Quality Engineering & Management Module 4
Measures of Location Average: X-bar Median: X~ Mode: M Measures
of Dispersion
Standard Deviation Range
2012 from "A First Course in Quality Engineering: Integrating
Statistical and Management Methods of Quality" by K.S.
Krishnamoorthi. Reproduced by permission of Taylor and Francis
Group, LLC, a division of Informa plc.
-
TUM School of Management Production and Supply Chain Management
Prof Martin Grunow Technische Universitt Mnchen
Practice
Now let's do an exercise together in descriptive statistics.
Please complete the next "Practice" module before continuing
with the lecture.
Holly Ott Quality Engineering & Management Module 4
