Understanding Statistics and Parameters: A Guide for Students

In summary, A statistic is a calculation made on a sample, while a parameter is a property of the entire population from which the sample was taken. The sample mean is a statistic that approaches the population mean as the sample size increases.
  • #1
danago
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Hey. I just wanted to clear something up. My texbook often refers to statistics and parameters. Is a statistic simply a calculation made on a sample, whereas a parameter is a property of the whole property from which the sample was taken?

Thanks in advance,
Dan.
 
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  • #2
Yeah, basically. A common definition of "statistic" is "a function of a sample/observation." A parameter is a property of the underlying population distribution. For example, the sample mean is a statistic which, as the sample becomes large, approaches the population mean, which is a parameter.
 
  • #3
yep ok that answers my question :smile: thanks
 

1. What is the difference between statistic and parameter?

Statistic refers to a numerical value that summarizes a sample of data, while parameter refers to a numerical value that summarizes a population of data.

2. How are statistic and parameter used in data analysis?

Statistic is used to estimate an unknown parameter of the population based on a sample, while parameter is used to describe the characteristics of a population.

3. Can a statistic be equal to a parameter?

Yes, if the statistic is calculated from the entire population, it will be equal to the parameter.

4. Why is it important to differentiate between statistic and parameter?

It is important to differentiate between statistic and parameter because they serve different purposes in data analysis. Using the correct term can help avoid confusion and ensure accurate interpretation of results.

5. What are some examples of statistic and parameter?

An example of statistic could be the average income of a sample of 100 people, while an example of parameter could be the average income of the entire population. Other examples include sample standard deviation as a statistic and population standard deviation as a parameter.

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