Representativeness - what is this process?

concept of representation is common in statistical reporting and the preparation of speeches and reports.Perhaps without it is difficult to imagine any kind of presenting information on display.

representativeness - what is it?

representativeness reflects how the selected objects or any of the content and meaning of the data set from which they were selected.

Other definitions

concept of representativeness can be expanded in different contexts.But its meaning representation - a matching characteristics and properties of the selected units from the total population that accurately reflect the general characteristics of the entire database as a whole.

representative information is also defined as the ability to submit a sample data set of parameters and properties that are important in terms of the ongoing investigation.

representative sample

principle of sampling is the most important election and accurately displays the properties of a common set of data.It uses a variety of methods that allow you to get accurate results and an overview of the general population, using only selected materials that describe the quality of the data.

buy instagram followers

Thus, no need to learn all the stuff, and it suffices to consider selective representation.What is it?This sample of individual data in order to have an idea about the total mass of information.

them depending on how you distinguish as probabilistic and-probability.Probability - a selection of which is made by calculating the most important and interesting data are further representatives of the population.This is a deliberate choice or a random sample, however, justified its content.

-probability - is one form of random sampling, on the basis of the normal component of the lottery.In this case, the opinion of the person who makes such a selection.It uses a blind draw.

Probability sampling

probability sampling can also be divided into several types:

  • One of the most simple and clear principles - a convenience sample.For example, this method is often used during social surveys.This survey participants are not selected from the crowd for some certain signs, and information is made at the first 50 people who participated in it.
  • purposive sampling differ in that they have a number of requirements and conditions for the selection, but still rely on coincidence, not in pursuit of its goal of achieving a good statistics.
  • sample on the basis of quotas - it is one of the variations-probability sample that is often used to study large data sets.For her, it used a variety of conditions and norms.Selected objects to match them.That is an example of social survey suggests that 100 people will be interviewed, but only the opinion of a number of people that will meet the requirements, will be considered in the preparation of statistical reports.

probability sample

for probability samples is calculated a number of parameters, which objects in the sample will meet, among them a number of ways it can be elected to the facts and data that will be presented as the representativeness of the sample data.These methods calculate the necessary data can be:

  • simple random sampling.It lies in the fact that among the selected segment completely randomly selected lottery required amount of data that will be a representative sample.
  • systematic and random sampling makes it possible to create a system of calculating the necessary data on the basis of a random segment.Thus, if the first random number that indicates the serial number of the data selected from the general population, is 5, then the subsequent data to be selected can be, for example, 15, 25, 35 and so on.This example clearly explains that even a random selection may be based on systematic calculations, the necessary input data.

sample of consumers

Meaningful sampling - a method that consists in considering each individual segment, and on the basis of its evaluation, a set of reflecting the characteristics and properties of a common database.Thus it recruited more data conforming to a representative sample.You can easily select a number of options that will not be included in the total number, without losing the quality of the selected data representing the general population.In this way, the representativeness of the results of the study determined.

sample size

Last issue that must be addressed - it is the sample size for the representativeness of the population.The sample size does not always depend on the number of sources in the general population.However, the representativeness of sample depends on how many segments should be eventually divided result.The more segments, the more data gets into productive sample.If the results require a generic term and does not require specifics, then, respectively, the sample becomes smaller, because, without going into details, the information described in more superficial, and therefore this article will be shared.

concept of representativeness errors

Error representativeness - is the specific differences between the characteristics of the population and sample data.In carrying out any sampling is absolutely impossible to get accurate data as the full study population and sample represented only part of the information and options, while a more detailed study is possible only in the study of the entire set.Thus, some unavoidable errors and mistakes.

kinds of errors

There are some errors that arise in the preparation of a representative sample:

  • Systematic.
  • Random.
  • deliberate.
  • Unintentional.
  • standard.
  • Limit.

reason for the appearance of random errors can be discontinuous nature of the study the total population.Usually, the random error of representativeness has a small size and character.

Systematic errors occur in between the violation of the rules of selection of data from the general population.

average error - the difference between the average values ​​of the samples and the basic set.It does not depend on the number of units in the sample.It is inversely proportional to the volume of the sample.Then the larger the volume, the lower the value of the average error.

Error limit - is the largest possible difference between the average value will make the sample and the total aggregate.This error is characterized as the most probable errors under the given conditions of their occurrence.

intentional and unintentional errors of representativeness

offset error data are intentional and unintentional.

then causes the appearance of a deliberate error is an approach to the selection of the data by the method of determining trends.Unintentional errors arise at the stage of preparation of sample survey, the formation of a representative sample.To avoid such errors, you must create a good basis for the sampling, compile lists of sampling units.It must be fully consistent with the objectives of the sampling, to be credible, covering all aspects of the study.

validity, reliability and representativeness.Calculation errors

calculation error of representativeness (mm) the arithmetic mean value (M).

Standard deviation: sample size (& gt; 30).

Error representativeness (Mp) and relative value (P): the number of samples (n & gt; 30).

In the case when it is necessary to study the collection, wherein the amount of the sample is small and is less than 30 units, then the number of cases will be less than one unit.

The error directly proportional to the volume of the sample.The representativeness of data and the calculation of the degree of the possibility of drawing up an accurate forecast reflects a certain amount limit mistakes.

Representative of

not only in the evaluation process of presenting information using a representative sample, but also the person receiving the information, the system uses a representative.Thus, brain processes certain amount of information, creating a representative sample of the entire flow of information in order to efficiently and quickly assess the submitted data, and understand the subject matter.Answer the question: "representative - what is it?" - On the scale of the human mind is pretty simple.To do this, the brain uses all subordinate to the senses, depending on what kind of information should be separated from the general flow.Thus, the distinction:

  • visual representational system where organs are utilized visual perception of the eye.People often use a similar system, called visuals.With this system, the person processes the information in the form of images.
  • Auditory representational system.The main body is used - this is a rumor.The information supplied in the form of speech or audio files, it is processed by the system.People are more receptive to information on the hearing, called audialami.
  • kinesthetic representational system is processing the flow of information by sensing it with the olfactory and tactile channels.

  • Digital representational system is used together with others as a means of obtaining information from the outside.This subjective perception and logical interpretation of the data.

So representation - what is it?Simple sample from a set or an essential procedure for the processing of information?We can say that the representativeness largely determines our perception of data flows, helping to isolate from it the most compelling and important.