Transcript STATISTICS

BPT 2423 – STATISTICAL PROCESS CONTROL
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Definition of Statistics
Populations versus Samples
Data Collection
Data Analysis
 Graphical & Analytical
Measurements
 Accuracy, Precision & Error
Central Limit Theorem
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Recall or review basic statistical concepts
Understand how to graphically and analytically
study a process by using statistics
Explain how to create and intercept a frequency
diagram and a histogram
Able to calculate the mean, median, mode,
range and standard deviation for a given set of
numbers
Discuss the importance of the normal curve and
the central limit theorem in quality assurance
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If things were done right just 99.9% of the time, then
we’d have to accept:
One hour of unsafe drinking water per month
 20,000 incorrect drug prescriptions per year
 500 incorrect surgical operations each week
 22,000 checks deducted form the wrong bank accounts per hour
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Each of the above statistics deals with the quality of
life as we know it. We use statistics every day to define
our expectations of life around us. Statistics, when
used in quality assurance, define the expectations that
the consumer and the designer have for the process.
Processes and products are studied using statistics.
STATISTICS : the collection, tabulation, analysis,
interpretation and presentation of numerical data.
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Provide a viable method of supporting or clarifying a
topic under discussion
Misuses of statistics have lead people to distrust them
completely
Correctly applied statistics are the key that unlocks an
understanding of process and system performance.
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A population is a collection of all possible elements,
values or items associated with a situation
Example : Insurance forms at doctor’s office must be process in a
day
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A sample is a subset of elements or measurements taken
from a population
Example : The doctor’s office may wish to sample 10 insurance
claim forms per week to check the forms for completeness.
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This smaller group of data is easier to collect, analyze and
interpret. A sample will represent the population as long
as the sample is RANDOM and UNBIASED.
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In a random sample, each item in the population has the
same opportunity to be selected
In order to interpret and use the information, it is critical
to know:
 How many were sampled
 Validity of a sample
 The size of the whole group
 The conditions under which the
survey was made
2 types of statistics exist :
 Deductive statistics – describe a population or complete
group of data
 Inductive statistics – a limited amount of data or a
representative sample of the population
 In quality control, 2 types of numerical data can be
collected:
Variable
Attribute
Those quality
characteristics that
can be measured
Tend to be
CONTINUOUS
(measured value can
take on any value
within a range) in
nature
VARIABLES DATA
Those quality
characteristics that
are observed to be
either present or
absent, conforming or
nonconforming
Primarily are DISCRETE
data (countable using
whole numbers)
ATTRIBUTES DATA
Frequency Diagrams
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Shows the number of times each
of the measured value occurred
when the data were collected
Score
Frequency
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Histograms
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Data are grouped into cells
Ungrouped data –
without any order
data
are
Grouped data – group together on
the basis of when the values were
taken or observed
MEAN
 The mean of a series of measurements is determined by
adding the values together and then dividing this sum
by the total number of values.
Exercise :
Data represent thickness measurement (in mm) of the clutch plate.
0.0625, 0.0626, 0.0624, 0.0625,
0.0627
Calculate the mean value.
MEDIAN
 The median is the value that divides an ordered series
of numbers so that there is an equal number of values
on either side of the center.
Exercise :
Determining the median for a set of numbers below:
Question 1
23, 25, 26, 27, 28, 29, 25, 22, 24, 24, 25, 26, 25
Question 2
1, 2, 4, 1, 5, 2, 6, 7
MODE
 The mode is the most frequently occurring number in a
group of values
Exercise :
Determine mode value.
Question 1
100, 101, 103, 104, 106, 107
Question 2
23, 25, 26, 25, 28, 25, 22, 24, 24, 25, 26
Question 3
658, 659, 659, 659, 670, 670, 671, 670, 672,
674, 674, 672, 672
The Relationship Among the Mean, Median and Mode
Symmetrical
Skewed Left
Skewed Right
Mean, Median and Mode are the statistical values that
define the center of a distribution, commonly called the
measures of central tendency.
RANGE
 Is the difference between the highest value in a series of
values or sample and the lowest value in that same
series
R = X high – X low
 Range value describes how far the data spread
STANDARD DEVIATION
 Shows the dispersion of the data within the distribution
Sample , s =
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Range and standard deviation are two measurements
that enable the investigator to determine the spread of
the data
These two describe where the data are dispersed on
either side of a central value, often referred to as
measures of dispersion.
Exercise :
At an automobile-testing ground, a new type of automobile was tested for
gas mileage. Seven cars, a sample of a much larger production run, were
driven under typical conditions to determine the number of miles per
gallon the cars got. The following miles-per-gallon readings were obtained:
36, 35, 39, 40, 35, 38, 41
Calculate the sample range and standard deviation.
ACCURACY
 Refers to how far from the
actual or real value the
measurement is
PRECISION
 Is the ability to repeat a series
of measurements and get the
same value each time
ERROR
 Is considered to be the
difference between a value
measured and the true value
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States that a group of sample averages tends to be
normally distributed; as the sample size (n) increases,
this tendency toward normality improves.