Pemodelan Kualitas Proses
Kode Matakuliah
Pertemuan
: I0092 – Statistik Pengendalian Kualitas
:2
Learning Objectives
2
Stem-and-Leaf Display
•Easy to find percentiles of the data; see page 43
3
Plot of Data in Time Order
Marginal plot
produced by
MINITAB
•Also called a run chart
4
Histograms – Useful for large data sets
•Group values of the variable into bins, then count the
number of observations that fall into each bin
•Plot frequency (or relative frequency) versus the values of
the variable
5
Histogram
for discrete
data
6
7
Numerical Summary of Data
8
9
10
The Box Plot
(or Box-and-Whisker Plot)
11
Comparative Box Plots
12
Probability Distributions
13
14
Sometimes called a
probability mass function
Sometimes called a
probability density function
Will see many examples in the text
15
16
17
18
19
20
21
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The Hypergeometric Distribution
23
24
The Binomial Distribution
Basis is in Bernoulli trials
The random variable x is the number of successes out of n
Bernoulli trials with constant probability of success p on each trial
25
26
27
28
The Poisson Distribution
Frequently used as a model for count data
29
30
The Pascal Distribution
The random variable x is the number of Bernoulli trials upon
which the rth success occurs
31
• When r = 1 the Pascal distribution is known as
the geometric distribution
• The geometric distribution has many useful
applications in SQC
32
The Normal Distribution
33
34
35
36
Original normal
distribution
Standard normal
distribution
37
38
39
• Practical interpretation – the sum of independent random
variables is approximately normally distributed regardless of
the distribution of each individual random variable in the sum
40
The Lognormal Distribution
41
42
43
The Exponential Distribution
44
Relationship between the Poisson and exponential distributions
45
The Gamma Distribution
46
• When r is an integer, the gamma distribution is the result of
summing r independently and identically exponential random
variables each with parameter λ
• The gamma distribution has many applications in reliability
engineering; see Example 2-121, text page 71
47
The Weibull Distribution
48
• When β = 1, the Weibull distribution reduces to
the exponential distribution
49
• Determining if a sample of data might reasonably be
assumed to come from a specific distribution
• Probability plots are available for various
distributions
• Easy to construct with computer software
(MINITAB)
• Subjective interpretation
50
Normal Probability Plot
51
52
Other Probability Plots
• What is a reasonable choice as a probability model
for these data?
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