The document discusses the key differences between population and sample in research. It defines population as the entire group being studied, while a sample is a subset of the population used to make inferences. Sample size is important for statistical analysis, as larger samples produce more accurate results. Random sampling is preferred as it gives each member of the population an equal chance of being selected for the sample.

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2. Population is complete actual/theoretical
collection of numerical values (scores) that are of
interest to the researcher.
Simbol = N (hurup besar)
Keseluruhan objek yang diteliti, baik
orang,benda, kejadian,nilai maupun yang hal-hal
yang diselidiki.
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3. Sample is a subset of population. Or a set of
observed scores from which the inferences of the
population is made.
Simbol = n (hurup kecil)
Bagian dari populasi yang akan diselidiki.
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4. Population Sample
• a population is the group • A sample is a set of data
of all items of interest to a drawn from the population.
statistics practitioner. • Potentially very large, but
• frequently very large; less than the population.
sometimes infinite. • E.g. a sample of 765
• E.g. All 5 million Jakarta voters exit polled on
voters. election day
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5. Population Sample
Subset
Statistic
Parameter
• Populations have Parameters,
• Samples have Statistics.
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6. • Statistical inference (Dugaan Statistik) is the process
of making an estimate, prediction, or decision about a
population based on a sample.
Population
Sample
Inference
Statistic
Parameter
What can we infer about a Population’s Parameters
based on a Sample’s Statistics?
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7. Contoh: Difference between
• Populasi: Seluruh population and
• Judul penelitian mahasiswa UPI sample:
“Keterlambatan (40.000 • sample is part of
population and its
Penyelesaian mahasiswa) function is to draw the
Studi di • Sample : 0,1% dari most accurate possible
kalangan populasi (400 picture of population
mahasiswa) from the limited data of
mahasiswa the sample.
UPI”. • Population consists of all
possible data.
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8. 1. Size of 3. Error
2. For 4. If we 5. Probability
sample is always exists
descriptive increase the of error
important to when we
statistics, sample size, always exists
make take the
size is not the error will in statistical
statistical sample from
important. decrease influence.
influence. population.
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9. Menurut Sutrisno Hadi, tidak ada
suatu ketepatan yang mutlak
berapa persen suatu sample harus
diambil dari populasi.
Beberapa faktor yang
membuat peneliti
mengambil sample:
(1) Biaya
(2) tenaga
(3) Waktu
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10. • Sampling adalah cara yang digunakan untuk mengambil
sample dan biasanya mengikuti teknik atau jenis tertentu.
1 Misalnya random sampling atau non-random sampling.
• Random sampling:
• each member of population has an equal chance of being
2 selected as sample.
• Without randomization the result of data analysis is
meaningless.
3
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11. Why is sample size
important?
To make statistical
inferences. The bigger
the sample size, the
more accurate the
conclusion.
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12. Kesalahan
sampling
Kesalahan
spesifikasi
teori
Kesalahan
Kesalahan
pengukuran /
random
measurement
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