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It checks bias in subsequent selections of samples

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Q: Why systematic sampling is not good for periodic data?
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Advantages and disadvantages of systematic sampling?

Advantages 1.It is very simple to use. 2.It also saves time and cost. 3.It checks bias in subsequent selections of samples. 4.Its variances are most often smaller than other alternative sampling technique,when it is suitable to use. Disadvantages 1.There is the possibility of losing vital information from the population. 2.It may not be possible to select the required sample size if the population is too small. 3.It may not be good for periodic data.


Why its is necessary to use sampling in statistical investigation?

Sampling gives good insight of the choosen sample


How to reduce sampling error?

The only way to get rid of sampling error is to use the entire population under study. This is usually impossible, so the next best thing is to use large samples and good sampling methods.


What are the different non-probability sampling techniques?

The related web sites give a good idea of the types of non-random sampling. These include snowball, convenience, quota, self-selection, diversity, expert, and others. Non-randon sampling is usually done because it is less expensive, easier, and quicker than random sampling.


When graphing why should you draw a smooth line that reflects the general patter rather that automatically connect the data points?

It is not true to say that you should automatically draw a smooth line. It depends on what you are attempting to do. A smooth line may be a good indicator of a trend but such a line is useless if you want to find out whether or not there is any periodicity in the data. For the latter you must join the data points and look for periodic patterns.

Related questions

Advantages and disadvantages of systematic sampling?

Advantages 1.It is very simple to use. 2.It also saves time and cost. 3.It checks bias in subsequent selections of samples. 4.Its variances are most often smaller than other alternative sampling technique,when it is suitable to use. Disadvantages 1.There is the possibility of losing vital information from the population. 2.It may not be possible to select the required sample size if the population is too small. 3.It may not be good for periodic data.


What is the significance of sampling in research and what are the characteristics of a good sample?

Sampling is important as data collected is used to test the hypothesis. A good sample is a true representation of the general population. In addition, it should be flexible and focus on the research objectives.


Example of panel sampling?

A good example to panel sampling will be sampling the performance of a group of companies in a specified region. This way they the samples can be revisited at a later stage thus panel sampling.


Why its is necessary to use sampling in statistical investigation?

Sampling gives good insight of the choosen sample


Why is it difficult to have a good Philippine president?

Systematic corruption


Systematic desensitization and what utilizes relaxation?

Is systematic desnsitization effective in treating children and adolescents? maybe a bubblebath? a good book?


How to reduce sampling error?

The only way to get rid of sampling error is to use the entire population under study. This is usually impossible, so the next best thing is to use large samples and good sampling methods.


What is multiple sampling in statistics?

watch house of anubis very good


How do you get sample using universal sampling technique?

try researching about total enumeration technique... it's the other name for universal sampling technique ^_^ Good luck..


Which method is good for heterogeneous population of sampling?

Type your answer here... convenient samplign


What are the Characteristics of good title?

easy to modify.or it should be brief and systematic


What are the different non-probability sampling techniques?

The related web sites give a good idea of the types of non-random sampling. These include snowball, convenience, quota, self-selection, diversity, expert, and others. Non-randon sampling is usually done because it is less expensive, easier, and quicker than random sampling.