Analisis data upload 1 0
ANALISIS DATA
SMT 310
retnosubekti@uny.ac.id
Motivasi
Memahami analisis eksplorasi dan
konfirmasi
Landasan statistika deskriptif dan
inferensi
Bersinergi dengan komputasi statistik
untuk meng-upgrade kemampuan
analisis data
Deskripsi
Penyusunan dan rangkuman data
numerik
Penyajian data univariat
Transformasi data
Sampel acak
Statistika konfirmasi
Analisis variansi
Hubungan antara dua variabel
Analisis data kategorik
Referensi
Erickson, Bonnie H & Nosanchuk. 1987.
Memahami Data : Statistika untuk Ilmu
Sosial. (terjemahan RK. Sembiring &
Manase Malo). Jakarta: LP3ES
Griffiths D., Stirling W.D, Weldon K.L .
1998. Understanding Data : Principles
and Practice of Statistics. Brisbane : John
Willey & Sons
Kontrak
Penilaian
Bobot :
Tugas : 20%
Kuis
: 15%
Usip : 25%
Uas
: 40%
REVIEW
STATISTIKA ?
STATISTIK ?
STATISTIKA DESKRIPTIF ?
Statistika inferensi
Populasi
Sampel
Parameter
Statistik
Data
Nilai ujian metode stastistik 20 orang
mahasiswa adalah :
91
50
73
74
55
86
70
43
47
80
40
85
64
61
58
95
52
67
83
92
Misalkan diketahui nilai ujian komputasi
statistika 50 mahasiswa
44,7 59,8 67,1 57,1
48,4 63,9 67,8 56,2
42,5 57,2 70,2
57
49,1 64,7 74,6 63,6
43,1 76,5 68,7 59,9
58,2 69,5 60,6 44,2
60 68,2 48,5
62,2 70,3
63,5 72,6
46 72,6
50 76,8
63 72,2 75,3
76 51,2
52
74 65,1
75 55,4 67,7
77 73,5 56,3 77,3
Banyaknya penjualan HP di suatu toko :
Merek
HP
Nokia
SE
Samsun
g
LG
Lain
Penjualan
56
45
32
22
45
Skala pengukuran
Nominal :
Ordinal:
Interval
:
Rasio
:
Contoh:
Nominal: jenis pekerjaan, warna
Ordinal: kepangkatan, tingkat pendidikan
Interval: tahun kalender (Masehi, Hijriyah),
temperatur
(Celcius, Fahrenheit)
Rasio: berat, panjang, isi
Statistika deskriptif
Metode atau cara-cara yang digunakan
untuk meringkas dan menyajikan data
dalam bentuk tabel, grafik atau
ringkasan numerik data.
Grafik Stem-and-leaf
Untuk menunjukkan bentuk distribusi data
Data berupa angka dengan minimal dua digit
Contoh (Data penghasilan buruh):
439
511555689
602334445556777889
7122344558
8349
92
Stem= 10, Leaf = 1
Intro…
Why study statistics?
Make decision without complete
informations
Understanding population, sample
Parameter, statistic
Descriptive and inferential statistics
glossary
A population is the collection of all items of interest
or under investigation
N represents the population size
A sample is an observed subset of the population
n represents the sample size
A parameter is a specific characteristic of a
population
Mean, Variance, Standard Deviation, Proportion, etc.
A statistic is a specific characteristic of a sample
Mean, Variance, Standard Deviation, Proportion, etc.
Population vs. Sample
Population
Sample
a b c d
ef gh i jk l m n
b c
o p q rs t u v w
g i n
x y z
o r u
y
Values calculated using
population data are called
parameters
Values computed from sample
data are called statistics
Examples of Populations
Incomes of all families living in yogyakarta
All women with pregnancy problem.
Grade point averages of all the students in
your university
…
Random sampling
Simple random sampling is a procedure in which
each member of the population is chosen
strictly by chance,
each member of the population is equally
likely to be chosen, and
every possible sample of n objects is equally
likely to be chosen
The resulting sample is called a random sample
Descriptive and Inferential Statistics
Two branches of statistics:
Descriptive statistics
Collecting, summarizing, and processing
data to transform data into information
Inferential statistics
Provide the bases for predictions, forecasts,
and estimates that are used to transform
information into knowledge and decision
Descriptive Statistics
Collect data
e.g., Survey
Present data
e.g., Tables and graphs
Summarize data
e.g., Sample mean =
�X
n
i
Inferential Statistics
Estimation
e.g., Estimate the population
mean weight using the
sample mean weight
Hypothesis testing
e.g., Test the claim that the
population mean weight is
120 pounds
Inference is the process of drawing conclusions or making decisions about a
population based on sample results
The Decision Making
Process
Decision
Knowledge
Experience, Theory,
Literature, Inferential
Statistics, Computers
Information
Descriptive Statistics,
Probability, Computers
Begin Here:
Identify the
Problem
Data
SMT 310
retnosubekti@uny.ac.id
Motivasi
Memahami analisis eksplorasi dan
konfirmasi
Landasan statistika deskriptif dan
inferensi
Bersinergi dengan komputasi statistik
untuk meng-upgrade kemampuan
analisis data
Deskripsi
Penyusunan dan rangkuman data
numerik
Penyajian data univariat
Transformasi data
Sampel acak
Statistika konfirmasi
Analisis variansi
Hubungan antara dua variabel
Analisis data kategorik
Referensi
Erickson, Bonnie H & Nosanchuk. 1987.
Memahami Data : Statistika untuk Ilmu
Sosial. (terjemahan RK. Sembiring &
Manase Malo). Jakarta: LP3ES
Griffiths D., Stirling W.D, Weldon K.L .
1998. Understanding Data : Principles
and Practice of Statistics. Brisbane : John
Willey & Sons
Kontrak
Penilaian
Bobot :
Tugas : 20%
Kuis
: 15%
Usip : 25%
Uas
: 40%
REVIEW
STATISTIKA ?
STATISTIK ?
STATISTIKA DESKRIPTIF ?
Statistika inferensi
Populasi
Sampel
Parameter
Statistik
Data
Nilai ujian metode stastistik 20 orang
mahasiswa adalah :
91
50
73
74
55
86
70
43
47
80
40
85
64
61
58
95
52
67
83
92
Misalkan diketahui nilai ujian komputasi
statistika 50 mahasiswa
44,7 59,8 67,1 57,1
48,4 63,9 67,8 56,2
42,5 57,2 70,2
57
49,1 64,7 74,6 63,6
43,1 76,5 68,7 59,9
58,2 69,5 60,6 44,2
60 68,2 48,5
62,2 70,3
63,5 72,6
46 72,6
50 76,8
63 72,2 75,3
76 51,2
52
74 65,1
75 55,4 67,7
77 73,5 56,3 77,3
Banyaknya penjualan HP di suatu toko :
Merek
HP
Nokia
SE
Samsun
g
LG
Lain
Penjualan
56
45
32
22
45
Skala pengukuran
Nominal :
Ordinal:
Interval
:
Rasio
:
Contoh:
Nominal: jenis pekerjaan, warna
Ordinal: kepangkatan, tingkat pendidikan
Interval: tahun kalender (Masehi, Hijriyah),
temperatur
(Celcius, Fahrenheit)
Rasio: berat, panjang, isi
Statistika deskriptif
Metode atau cara-cara yang digunakan
untuk meringkas dan menyajikan data
dalam bentuk tabel, grafik atau
ringkasan numerik data.
Grafik Stem-and-leaf
Untuk menunjukkan bentuk distribusi data
Data berupa angka dengan minimal dua digit
Contoh (Data penghasilan buruh):
439
511555689
602334445556777889
7122344558
8349
92
Stem= 10, Leaf = 1
Intro…
Why study statistics?
Make decision without complete
informations
Understanding population, sample
Parameter, statistic
Descriptive and inferential statistics
glossary
A population is the collection of all items of interest
or under investigation
N represents the population size
A sample is an observed subset of the population
n represents the sample size
A parameter is a specific characteristic of a
population
Mean, Variance, Standard Deviation, Proportion, etc.
A statistic is a specific characteristic of a sample
Mean, Variance, Standard Deviation, Proportion, etc.
Population vs. Sample
Population
Sample
a b c d
ef gh i jk l m n
b c
o p q rs t u v w
g i n
x y z
o r u
y
Values calculated using
population data are called
parameters
Values computed from sample
data are called statistics
Examples of Populations
Incomes of all families living in yogyakarta
All women with pregnancy problem.
Grade point averages of all the students in
your university
…
Random sampling
Simple random sampling is a procedure in which
each member of the population is chosen
strictly by chance,
each member of the population is equally
likely to be chosen, and
every possible sample of n objects is equally
likely to be chosen
The resulting sample is called a random sample
Descriptive and Inferential Statistics
Two branches of statistics:
Descriptive statistics
Collecting, summarizing, and processing
data to transform data into information
Inferential statistics
Provide the bases for predictions, forecasts,
and estimates that are used to transform
information into knowledge and decision
Descriptive Statistics
Collect data
e.g., Survey
Present data
e.g., Tables and graphs
Summarize data
e.g., Sample mean =
�X
n
i
Inferential Statistics
Estimation
e.g., Estimate the population
mean weight using the
sample mean weight
Hypothesis testing
e.g., Test the claim that the
population mean weight is
120 pounds
Inference is the process of drawing conclusions or making decisions about a
population based on sample results
The Decision Making
Process
Decision
Knowledge
Experience, Theory,
Literature, Inferential
Statistics, Computers
Information
Descriptive Statistics,
Probability, Computers
Begin Here:
Identify the
Problem
Data