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Glossary
These is glossary of research key terms. This glossary is intended as an aid to professionals and non-professionals who find the world of research somewhat intimidating. While it is impossible to cover all the terms that can be confusing, this document briefly defines some of the more common terms and concepts.

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Term Definition
Sampel

Pendapat Sugiyono, sampel adalah bagian dari jumlah dan karakteristik yang dimiliki oleh populasi tersebut. Contoh: Karena jumlah populasi tidak diketahui tidak terhingga, maka jumlah penentuan sampel dilakukan berdasarkan pendapat Nares K. Malhotru (1993:622), yang menyatakan bahwa jumlah sampel atau responden paling sedikit empat atau lima kali jumlah sub variabel/item yang digunakan dalam penelitian.

 

 
Sample
1. A subset of population elements. In some usages, contrasts with population. 2. a selection of units from a population (universe). Of particular importance is how the sample was selected (see simple random sample [SRS]). 3. subset of the population used for study.
 
Sampling
1. The practice of choosing a subset of population elements to study instead of the entire population. In general, we sample because (a) it's cheaper; (b) in some cases the population is theoretically infinite. There are two basic kinds of sampling: probability and non-probability. 2. The process of selecting a subgroup of a population to represent the entire population. There are several different types of sampling, including:
 
Sampling biasDistortion that occurs when a sample is not representative of the population from which it was drawn.
 
Sampling Error
1. A difference, due to sampling, between a population parameter and the corresponding sample statistic. For example, the average age of a population might be 25 years, but a given sample might yield an average of 26 because, by chance, more old people were selected than the population proportion. 2. The fluctuation in the value of a statistic from different samples drawn from the same population. 3. Random or unsystematic error resulting from selecting a sample from a population. 4. the error in estimates of a population due to the variation possible in samples
 
Sampling Frame
1. The sampling frame is a specific list of names (or other identifying codes) of the cases to be sampled. Usually, this is supposed to be the same as the population. For example, when you study IBM, you start by obtaining a list of all IBM employees. This is the sampling frame. If your list is not complete (e.g., it omits top management), your results may not be valid in the sense of generalizing to all of IBM. 2. A list of the entire population eligible to be included within the specific parameters of a research study. A researcher must have a sampling frame in order to generate a random sample.
 
Sampling RatioThe sampling ratio is the size of the sample divided by the size of the population.
 


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