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Statistics is the science of making effective use of numerical data relating to groups of individuals or experiments sampling is an important to statistics because It deals with all aspects of this including not only the collection analysis and interpretation of such data but also the planning of the collection of data

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Q: Why are random samples so important in Statistics?
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Why do Social Scientists gather data from samples instead of populations?

It is simple statistics. It would be almost impossible to survey an entire population, so they apply a simple random sample in which each person in the population receives a numerical value (001 - 999 for example). Then they use a random number generator on a calculator or use a random digit table to choose an appropriate amount of people to be sampled. It is more cost effective and easier to do it this way, yet still represents the population fairly accurately.


What is the meaning of finite population in statistics?

Finite populations mean a limited size population. Sometimes, a limited population is very large, so it may be treated as an infinite population, for statistical inferences. In statistics, the population size may not be known. The assumption of infinite or finite population is important. If a survey is being conducted in a completely random manner, the same person could be surveyed twice. The chance of this occurring diminishes as the population increases.


Why the random sample is important in design of experiment?

There are circumstances when it is important and others when it is not. If, for example, you wanted a sample of all schools in the country, it would make more sense to go for cluster sampling. A lot of market research work will require quota sampling. So the supremacy of a random sample is a myth.


What are some uses of statistics in your life?

statistics is used in all aspect of life. so which ever one human finds himself it is alwayz beter to give it a name examples are agricultural statistics, insurance statistics, actuarial statistics,educational statistics,financial statistics etc


Why is statistical significance important?

Because there are so many things that happen - some predictably, some coincidentally - that all fall into the category of random "chance" - it's this way one time, that way the next. Statistics are carefully calculated to have a cut-off point, below which is considered to be within the category of "random". Above that figure, it is more frequent than "random" can explain. At that point, it becomes - to a greater or lesser degree - "statistically significant". A simplistic example: If a child has a school year 180 days long, and the child is "home sick" seven out of those 180 days, that is within the realm of random. If the child is "home sick" 57 of those 180 days, that is "statistically significant".

Related questions

Will all random samples from a given population have the same mean?

Data from random samples will not always include the same values. Values are chosen randomly and they may or may not be the same. So means will vary among random samples.


Why is random sampling so important for research?

sampling is very important for researcher


Why do Social Scientists gather data from samples instead of populations?

It is simple statistics. It would be almost impossible to survey an entire population, so they apply a simple random sample in which each person in the population receives a numerical value (001 - 999 for example). Then they use a random number generator on a calculator or use a random digit table to choose an appropriate amount of people to be sampled. It is more cost effective and easier to do it this way, yet still represents the population fairly accurately.


How many simple random samples of size 5 can be obtained from a population whose size is 38?

You wouldn't want to use the same item twice, so just divide 38/5 = 7+ ... you can get 7 samples of size 5.


Why don't psychologists use random samples often?

It is impossible to obtain a truly random sample. Psychologists will endeavour however to have a sample as random as is possible given the constraints of the study. Indeed there are often factors that make it difficult to obtain randomness, for example geographic location. So to answer your question, it is not that psychologists avoid the random sample, in fact, they prefer it when it is obtainable however this is often not the case.


Does Cody Simpson like so random?

i think Cody Simpson does like so random because he went to sing in so random i think he likes so random


What is the use of the Gamma distribution?

It is very frequently used in statistics. First of all, multiplying a Chi-square random variable by a constant you obtain a Gamma random variable. So, for example, most estimates of variance obtained in inferential statistics have a Gamma distribution. The Gamma distribution can also be obtained by summing exponential random variables. So, the Gamma distribution pops out in models where the exponential distribution is used (e.g. reliability, credit risk). It is also used for Internet traffic modeling. See the StatLect entry (link below) for an introduction.


What did ancient Egyptians put dead bodies in?

In a tomb.... then they buried the important people in the pyramids and the not so important people any random place in the dessert ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;) ;)


Does Emma on Jessie play on so random?

She is on so random


The importance of statistics?

Statistics is very important because it helps companies focus on the bigger picture, helps in ensuring quality and helps in making connections. Statistics is very important in many companies because it helps in the streamlining and the production process.


What variable are these samples if There are 8 participants in both samplesbut sample 1 are younger and sample 2 are older?

Variables are variable and samples are samples. Variables are not samples so the question has no meaning.


What is the meaning of finite population in statistics?

Finite populations mean a limited size population. Sometimes, a limited population is very large, so it may be treated as an infinite population, for statistical inferences. In statistics, the population size may not be known. The assumption of infinite or finite population is important. If a survey is being conducted in a completely random manner, the same person could be surveyed twice. The chance of this occurring diminishes as the population increases.