whole population, as the population size is quite small (14 students t translation - whole population, as the population size is quite small (14 students t Indonesian how to say

whole population, as the population

whole population, as the population size is quite small (14 students this
year). Sampling the whole population is known as a census. It is also possible
to (attempt to) sample even a large population given enough
resources. Governments, for example, regularly conduct a census of their
population, although, as recent examples in the United States and the
United Kingdom have shown, this process is not without problems and
not all members of the population are actually reached. In most cases,
we do not have the resources to study the whole population and will
need to sample. It is important to remember that we can only generalise
to a population we have actually sampled from. And therefore some
thought about exactly what our population is going to be is warranted.

Decide how to sample from the population
In most cases we will need to take a sample from our population. We will
then usually want to generalise the results we find in our sample to our
population. After all, a survey of the voting intentions of a sample of
1,000 people would not be very useful if we couldn’t generalise our findings
from that sample to voters as a whole! In order for us to be able to
generalise, we need to have an unbiased sample of the population, which
means that we want our sample to be representative of the population
we are studying, and not skewed towards one group or another. If we
were trying to generalise to all 10-year-olds, for example, we wouldn’t
want to sample only all-girls schools. The best way of ensuring that our
sample is unbiased is by using probability sampling methods.
The most well-known of these is simple random sampling. In a typical
simple random sample everyone in the population has exactly the same
chance of being included in the sample. This is because the sample is
drawn at random from the population (for example, by putting names in
a hat or, more typically nowadays, by using random number generators).
That makes it the most unbiased form of sampling, and this is the
method used to draw lottery numbers, for example. Saying that this is
the most unbiased sampling method would suggest that it is a good idea
to attempt to use simple random sampling at all times. However, when
one looks at actual educational research, it is clear that the majority of
studies do not in fact use this method. Why is this? There are a number
of reasons, some good, some less so.
One good reason is that while simple random samples are excellent for
generalising to the population as a whole, we might in some cases want
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whole population, as the population size is quite small (14 students thisyear). Sampling the whole population is known as a census. It is also possibleto (attempt to) sample even a large population given enoughresources. Governments, for example, regularly conduct a census of theirpopulation, although, as recent examples in the United States and theUnited Kingdom have shown, this process is not without problems andnot all members of the population are actually reached. In most cases,we do not have the resources to study the whole population and willneed to sample. It is important to remember that we can only generaliseto a population we have actually sampled from. And therefore somethought about exactly what our population is going to be is warranted.Decide how to sample from the populationIn most cases we will need to take a sample from our population. We willthen usually want to generalise the results we find in our sample to ourpopulation. After all, a survey of the voting intentions of a sample of1,000 people would not be very useful if we couldn’t generalise our findingsfrom that sample to voters as a whole! In order for us to be able togeneralise, we need to have an unbiased sample of the population, whichmeans that we want our sample to be representative of the populationwe are studying, and not skewed towards one group or another. If wewere trying to generalise to all 10-year-olds, for example, we wouldn’twant to sample only all-girls schools. The best way of ensuring that oursample is unbiased is by using probability sampling methods.The most well-known of these is simple random sampling. In a typicalsimple random sample everyone in the population has exactly the samechance of being included in the sample. This is because the sample isdrawn at random from the population (for example, by putting names ina hat or, more typically nowadays, by using random number generators).That makes it the most unbiased form of sampling, and this is themethod used to draw lottery numbers, for example. Saying that this isthe most unbiased sampling method would suggest that it is a good ideato attempt to use simple random sampling at all times. However, whenone looks at actual educational research, it is clear that the majority ofstudies do not in fact use this method. Why is this? There are a numberof reasons, some good, some less so.One good reason is that while simple random samples are excellent forgeneralising to the population as a whole, we might in some cases want
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seluruh populasi, sebagai ukuran populasi cukup kecil (14 siswa ini
tahun). Sampling seluruh penduduk dikenal sebagai sensus. Hal ini juga memungkinkan
untuk (berusaha) sampel bahkan populasi besar diberikan cukup
sumber daya. Pemerintah, misalnya, secara rutin melakukan sensus dari mereka
penduduk, meskipun, seperti contoh terbaru di Amerika Serikat dan
Inggris telah menunjukkan, proses ini bukan tanpa masalah dan
tidak semua anggota populasi sebenarnya tercapai. Dalam kebanyakan kasus,
kita tidak memiliki sumber daya untuk mempelajari seluruh populasi dan akan
perlu sampel. Penting untuk diingat bahwa kita hanya bisa menggeneralisasi
untuk populasi kita telah benar-benar sampel dari. Dan karena itu beberapa
berpikir tentang apa yang sebenarnya terjadi populasi kita menjadi dibenarkan.

Tentukan bagaimana sampel dari populasi
Dalam kebanyakan kasus kita perlu mengambil sampel dari populasi kita. Kami akan
maka biasanya ingin menggeneralisasi hasil yang kita temukan dalam sampel kami untuk kami
penduduk. Setelah semua, survei niat suara dari sampel
1.000 orang tidak akan sangat berguna jika kita tidak bisa menyamaratakan temuan kami
dari sampel itu untuk pemilih secara keseluruhan! Agar kita dapat
menggeneralisasi, kita perlu memiliki sampel berisi dari populasi, yang
berarti bahwa kita ingin sampel kami untuk menjadi wakil dari populasi
kita belajar, dan tidak miring terhadap satu kelompok atau lainnya. Jika kita
mencoba untuk menggeneralisasi semua 10-year-olds, misalnya, kita tidak
ingin sampel sekolah hanya semua-gadis. Cara terbaik untuk memastikan bahwa kami
sampel berisi adalah dengan menggunakan metode probability sampling.
Yang paling terkenal ini adalah simple random sampling. Dalam khas
sederhana sampel acak orang dalam populasi memiliki persis sama
kesempatan yang termasuk dalam sampel. Hal ini karena sampel
diambil secara acak dari populasi (misalnya, dengan menempatkan nama dalam
topi atau, lebih biasanya saat ini, dengan menggunakan generator nomor acak).
Itu membuat bentuk yang paling berisi sampling, dan ini adalah
metode digunakan untuk menggambar nomor undian, misalnya. Mengatakan bahwa ini adalah
metode sampling yang paling berisi akan menyarankan bahwa itu adalah ide yang baik
untuk mencoba menggunakan simple random sampling setiap saat. Namun, ketika
kita melihat penelitian pendidikan yang sebenarnya, jelas bahwa mayoritas
studi pada kenyataannya tidak menggunakan metode ini. Kenapa ini? Ada sejumlah
alasan, beberapa baik, beberapa kurang begitu.
Salah satu alasan yang baik adalah bahwa sementara sampel acak sederhana sangat baik untuk
generalising untuk penduduk secara keseluruhan, kita mungkin dalam beberapa kasus ingin
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