In statistics there are two different ways of collecting data, namely census and sampling method.
Understanding the Census is a data collection if all elements of the population investigated one by one. The data obtained are the result of census processing is referred to as the actual data (true value), or often also called parameters. For example: the results of the census of 1981 gives the actual data regarding the population of Indonesia (the numbers by gender, by age, by education, in employment and religion), and civil servants census of 1974 provides the actual data on the amount by education, by region, central and so forth. agricultural and industrial census sensu, each providing actual data on the state of agriculture and industry issues.
It should be noted here is that the census is expensive and requires a lot of time and effort. Actually this is not an efficient way. Therefore, according to the UN recommendations (United Nations) to the state its members, the census in 1971, 1980, 1990 and 2000), while the industrial and agricultural census each only once in 5 years.
Understanding Sampling is a data collection form when the investigated sample from a population. The data obtained from the sampling is estimated data (estimated value). So, if of 100 companies will be investigated only 10 course, the outcome of the investigation is an estimate. For example: the estimated number of employees, the estimated amount of capital, the estimated amount of production, the average estimate of capital and others. If the value is calculated based on all elements of the population are called parameters, then the data is calculated based on the known sample statistics without statistical {s, s defined because statistics with statistical science is often called statistical}.
Advantages compared with Census Sampling, data collection using sampling method costs much less, not too much power, requires less time and can produce a wider range of data and detailed. In many of the problems faced, the method of data collection by sampling preferably with consideration of cost and time constraints as well as research that is detrimental.
Some sampling type, as follows:
Random sampling is the selection of the sampling elements randomized population (random). The selection is done by using the lottery, sweepstakes or a random number table (table of random number)
Simple random sampling is samplin where the selection is done in such a way elements of the population, so that each element has the same chance of being selected
Multistage random sampling is a sampling where the selection of the sample members element gradually.
Randim Cluster sampling is sampling where the elements consist of elements smaller yag called clusters. Cluster was selected as a sample, all elements must be examined one by one. Unlike the stratified random sampling where each stratum was sampled to make estimates in order to represent the parameters of the corresponding stratum.
Systematic Random Sampling is sampling where the selection of the first element chosen at random (random), while the next element selected systematically within k, where k = N / n. Do the following: select a random number from 1 to k.
Stratified random sampling is sampling where the selection of the sample members element is performed as follows:
first, the population split or divided into smaller population called the stratum. Making stratum should be homogeneous or relatively homogeneous, for example, be a Stratum k (k = 2.3 or more).
second, each stratum randomly drawn sample, then made estimates to represent the corresponding stratum.
Third, the estimate for the entire population of the combined formula used.
In inferential statistics, we want to know the description of certain characteristics of a population, but sometimes it is sometimes impossible and impractical to observe all objects / individuals that make up a population. Retail traders rice just study a handful of rice to determine the quality of rice now. Gold traders simply researching the former rubbing of the jewelry to determine the quality of gold jewelry. Environmental researchers looked only at a few milliliters of water to determine the quality of water in a river or lake. The question is, why not examine the whole, not the results will be better and more appropriate?
Given a researcher to conduct a full investigation by the limitations both in terms of cost, time, and so the research conducted to collect the desired information or data in accordance with the problems studied reached by taking the majority of the population, taking into account existing ketebatasan of researchers. Part of the population as a place to gather information called sample (sample).
Thus, the sample is part of the population that is selected by using certain rules, which are used to collect information / data that describe the nature or characteristics of the population owned.
From the definition, it is clear that the samples we take are used to describe the characteristics of a population, or in other words, the sample is used to generalize a population. Thus, the sample should really be representative in order to represent and reflect the characteristics of the population from which the sample was taken.
A researcher, rarely observe the entire population because of two reasons:
• Costs are too high and
• The population is dynamic, ie the elements of the population may change from time to time.
There are three main advantages of sampling:
• Lower costs,
• Collection of data faster, and
• It is possible to ensure uniformity and to improve the accuracy and quality of the data because the data set is smaller.
Types of samples
In the sample selection process there are two determining factors that play a role, namely:
• The presence or absence of randomization factor, and
• The role of people who choose to (take) the sample.
In the sampling process using randomization factors could include elements of chance, whereas the role of the sample selector can be objective and can also be subjective.
What is meant by an objective attitude in selecting the sample is a sample selection method that uses a specific method that is clear, so that if the sampling is done by others will be obtained results are not much different from the previous sampling, the suspect nature or characteristics of the population. So with sampling by using certain methods and obviously, will be obtained samples were consistent, meaning that if the sampling is done in abundance repeatedly to the same population under control in the sense that the result remains describe the nature or characteristics of the population, although the results are not exactly the same between the one another.
Subjective character in choosing the sample is a sample selection involving personal consideration of samplers to take a good sample according to his own version (version researcher). Thus obtained sample is biased samples, especially those who choose cotnoh sample has less background to the concept of statistics in particular the concept of sampling theory.
Definition Statistics
Statistics is a branch of applied mathematics that consists of theory and methods on how to collect, measure, classify, calculate, explain, synthesize, analyze, and interpret data obtained systematically.
Thus, therein consists of a set of procedures on how to:
• Collecting Data
• Summarizing Data
• Process the data
• Presenting Data
• Drawing conclusions and interpretation of the data based on the collection of data and analysis results
COMMENT :
In my opinion, the article is very clear and detailed in explaining about the census and sampling. Because the statistics are two different ways of collecting data, namely census and sampling method. And this way it's so important to be learned by students who are contracted statistics courses.
This article provides information that is very clear and easy to understand. This article presents the definition of the census is a data collection if all elements of the population investigated one by one. The data obtained are the result of census processing is referred to as the actual data (true value), or often also called parameters.
In this article also mentioned also what the definition of statistics so it is complete for a short article. This article presents the points in each topic so that these points can inform and summarize about the census and sampling that can facilitate readers to understand the topic sampling and census has been presented by this article or material.
Given a researcher to conduct a full investigation by the limitations both in terms of cost, time, and so the research conducted to collect the desired information or data in accordance with the problems studied reached by taking the majority of the population, taking into account existing ketebatasan of researchers. Part of the population as a place to gather information called sample (sample).
Thus, the sample is part of the population that is selected by using certain rules, which are used to collect information / data that describe the nature or characteristics of the population owned.
From the definition, it is clear that the samples we take are used to describe the characteristics of a population, or in other words, the sample is used to generalize a population. Thus, the sample should really be representative in order to represent and reflect the characteristics of the population from which the sample was taken.
Understanding the Census is a data collection if all elements of the population investigated one by one. The data obtained are the result of census processing is referred to as the actual data (true value), or often also called parameters. For example: the results of the census of 1981 gives the actual data regarding the population of Indonesia (the numbers by gender, by age, by education, in employment and religion), and civil servants census of 1974 provides the actual data on the amount by education, by region, central and so forth. agricultural and industrial census sensu, each providing actual data on the state of agriculture and industry issues.
It should be noted here is that the census is expensive and requires a lot of time and effort. Actually this is not an efficient way. Therefore, according to the UN recommendations (United Nations) to the state its members, the census in 1971, 1980, 1990 and 2000), while the industrial and agricultural census each only once in 5 years.
Understanding Sampling is a data collection form when the investigated sample from a population. The data obtained from the sampling is estimated data (estimated value). So, if of 100 companies will be investigated only 10 course, the outcome of the investigation is an estimate. For example: the estimated number of employees, the estimated amount of capital, the estimated amount of production, the average estimate of capital and others. If the value is calculated based on all elements of the population are called parameters, then the data is calculated based on the known sample statistics without statistical {s, s defined because statistics with statistical science is often called statistical}.
Advantages compared with Census Sampling, data collection using sampling method costs much less, not too much power, requires less time and can produce a wider range of data and detailed. In many of the problems faced, the method of data collection by sampling preferably with consideration of cost and time constraints as well as research that is detrimental.
Some sampling type, as follows:
Random sampling is the selection of the sampling elements randomized population (random). The selection is done by using the lottery, sweepstakes or a random number table (table of random number)
Simple random sampling is samplin where the selection is done in such a way elements of the population, so that each element has the same chance of being selected
Multistage random sampling is a sampling where the selection of the sample members element gradually.
Randim Cluster sampling is sampling where the elements consist of elements smaller yag called clusters. Cluster was selected as a sample, all elements must be examined one by one. Unlike the stratified random sampling where each stratum was sampled to make estimates in order to represent the parameters of the corresponding stratum.
Systematic Random Sampling is sampling where the selection of the first element chosen at random (random), while the next element selected systematically within k, where k = N / n. Do the following: select a random number from 1 to k.
Stratified random sampling is sampling where the selection of the sample members element is performed as follows:
first, the population split or divided into smaller population called the stratum. Making stratum should be homogeneous or relatively homogeneous, for example, be a Stratum k (k = 2.3 or more).
second, each stratum randomly drawn sample, then made estimates to represent the corresponding stratum.
Third, the estimate for the entire population of the combined formula used.
In inferential statistics, we want to know the description of certain characteristics of a population, but sometimes it is sometimes impossible and impractical to observe all objects / individuals that make up a population. Retail traders rice just study a handful of rice to determine the quality of rice now. Gold traders simply researching the former rubbing of the jewelry to determine the quality of gold jewelry. Environmental researchers looked only at a few milliliters of water to determine the quality of water in a river or lake. The question is, why not examine the whole, not the results will be better and more appropriate?
Given a researcher to conduct a full investigation by the limitations both in terms of cost, time, and so the research conducted to collect the desired information or data in accordance with the problems studied reached by taking the majority of the population, taking into account existing ketebatasan of researchers. Part of the population as a place to gather information called sample (sample).
Thus, the sample is part of the population that is selected by using certain rules, which are used to collect information / data that describe the nature or characteristics of the population owned.
From the definition, it is clear that the samples we take are used to describe the characteristics of a population, or in other words, the sample is used to generalize a population. Thus, the sample should really be representative in order to represent and reflect the characteristics of the population from which the sample was taken.
A researcher, rarely observe the entire population because of two reasons:
• Costs are too high and
• The population is dynamic, ie the elements of the population may change from time to time.
There are three main advantages of sampling:
• Lower costs,
• Collection of data faster, and
• It is possible to ensure uniformity and to improve the accuracy and quality of the data because the data set is smaller.
Types of samples
In the sample selection process there are two determining factors that play a role, namely:
• The presence or absence of randomization factor, and
• The role of people who choose to (take) the sample.
In the sampling process using randomization factors could include elements of chance, whereas the role of the sample selector can be objective and can also be subjective.
What is meant by an objective attitude in selecting the sample is a sample selection method that uses a specific method that is clear, so that if the sampling is done by others will be obtained results are not much different from the previous sampling, the suspect nature or characteristics of the population. So with sampling by using certain methods and obviously, will be obtained samples were consistent, meaning that if the sampling is done in abundance repeatedly to the same population under control in the sense that the result remains describe the nature or characteristics of the population, although the results are not exactly the same between the one another.
Subjective character in choosing the sample is a sample selection involving personal consideration of samplers to take a good sample according to his own version (version researcher). Thus obtained sample is biased samples, especially those who choose cotnoh sample has less background to the concept of statistics in particular the concept of sampling theory.
Definition Statistics
Statistics is a branch of applied mathematics that consists of theory and methods on how to collect, measure, classify, calculate, explain, synthesize, analyze, and interpret data obtained systematically.
Thus, therein consists of a set of procedures on how to:
• Collecting Data
• Summarizing Data
• Process the data
• Presenting Data
• Drawing conclusions and interpretation of the data based on the collection of data and analysis results
COMMENT :
In my opinion, the article is very clear and detailed in explaining about the census and sampling. Because the statistics are two different ways of collecting data, namely census and sampling method. And this way it's so important to be learned by students who are contracted statistics courses.
This article provides information that is very clear and easy to understand. This article presents the definition of the census is a data collection if all elements of the population investigated one by one. The data obtained are the result of census processing is referred to as the actual data (true value), or often also called parameters.
In this article also mentioned also what the definition of statistics so it is complete for a short article. This article presents the points in each topic so that these points can inform and summarize about the census and sampling that can facilitate readers to understand the topic sampling and census has been presented by this article or material.
Given a researcher to conduct a full investigation by the limitations both in terms of cost, time, and so the research conducted to collect the desired information or data in accordance with the problems studied reached by taking the majority of the population, taking into account existing ketebatasan of researchers. Part of the population as a place to gather information called sample (sample).
Thus, the sample is part of the population that is selected by using certain rules, which are used to collect information / data that describe the nature or characteristics of the population owned.
From the definition, it is clear that the samples we take are used to describe the characteristics of a population, or in other words, the sample is used to generalize a population. Thus, the sample should really be representative in order to represent and reflect the characteristics of the population from which the sample was taken.
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