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07 distr normal
1. DISTRIBUSI PELUANG KONTINU
• Distribusi Normal
• Distribusi Gamma
• Distribusi Eksponensial
• Distribusi Weilbull
• Distribusi t
• Distribusi F
• Distribusi Chi-square
2. DISTRIBUSI NORMAL
• Distribusi peluang kontinu terpenting dalam
statistika
• Kurva berbentuk bel
• Aplikatif dalam pengukuran fisik
• Nama lain: distribusi Gauss
6. CIRI KURVA NORMAL
• Letak modus di x = µ.
• Kurva simetris terhadap sumbu vertikal yang melalui rata-rata
µ.
• Kurva bertitik belok di x = µ ± σ, cekung ke bawah untuk µ - σ
< X < µ + σ dan cekung ke atas pada bagian lainnya.
• Sumbu horizontal merupakan garis asimtot yang dihampiri
kurva menuju kedua arah yang menjauh dari rata-rata.
• Luas daerah di bawah kurva dan di atas sumbu vertikal adalah
1.
7.
8. VARIANCE OF THE NORMAL DISTRIBUTION
• MEASURES THE SPREAD OF THE CURVE
Variance < Variance < Variance
Standard < Standard < Standard
Deviation Deviation Deviation
• MEASURE DISTANCE FROM THE MEAN () IN UNITS OF THE STANDARD
DEVIATION
11. CONTOH PENERAPAN DISTRIBUSI
NORMAL (1)
• A certain type of storage battery lasts on the average 3.0
years, with a standard deviation of 0.5 year. Assuming that
the battery lives are normally distributed, find the
probability that a given battery will last less than 2.3 years.
• An electrical firm manufacturers light bulbs that have a
length of life that is normally distributed with mean equal
to 800 hours and a standard deviation of 40 hours. Find the
probability that a bulb burns between 778 and 834 hours.
12. CONTOH PENERAPAN DISTRIBUSI
NORMAL (2)
• In an industrial process the diameter of a ball bearing
is an important component part. The buyer sets
specification on the diameter to be 3.0 ± 0.01 cm.
The implication is that no part falling outside these
specifications will be accepted. It is known that in the
process the diameter of a ball bearing has a normal
distribution with mean 3.0 and standard deviation
0.005. On the average, how many manufactured ball
bearings will be scrapped?
13. CONTOH PENERAPAN DISTRIBUSI
NORMAL (3)
• A certain machine makes electrical resistors
having a mean resistance of 40 ohms and a
standard deviation of 2 ohms. Assuming that
the resistance follows a normal distribution
and can be measured to any degree of
accuracy, what percentage of resistors will
have a resistance that exceeds 43 ohms?