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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.
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 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.
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".
