Q:

What is the difference between a parameter and a statistic?

A:

A statistic describes a sample, while a parameter describes an entire population. A sample is a smaller subset that is representative of a larger population.

The symbols differ when reporting statistics versus parameters. The average symbol for a statistic is an x with a line on top of it. For a parameter, the average is represented by the symbol μ. Since it is not always possible to collect every single observation in a population, sampling procedures are used to select a representative sample. Random sampling allows a statistician to calculate statistics about a sample and apply them to a population.


Is this answer helpful?

Similar Questions

  • Q:

    What is the sample mean formula?

    A:

    Sample mean is calculated by finding the sum of all terms in the selected sample and dividing this figure by the total number of terms. This formula is used to compute the average of the data collected.

    Full Answer >
    Filed Under:
  • Q:

    What is a good statistical sample size?

    A:

    A good statistical sample size is at least 100, and preferably more, participants. With a 100-participant sample size, the researcher has a margin of error of approximately 10 percent with a 95 percent confidence rating in the results. For the researcher to increase his confidence rating and reduce his margin of error he has to increase the size of the sample.

    Full Answer >
    Filed Under:
  • Q:

    What is the difference between sensitivity vs. specificity?

    A:

    The term sensitivity in epidemiology is a statistical measure on individuals who are positive, and they test positive in the tests. On the other hand, specificity refers to a statistical measure of individuals who tests negative and are truly negative.

    Full Answer >
    Filed Under:
  • Q:

    What is the difference between statistical significance and practical significance?

    A:

    Statistical significance shows the mathematical probability that a relationship between two or more variables exists, while practical significance refers to relationships between variables with real-world applications, according to California State University, Long Beach. Two or more variables do not need statistical significance to have practical significance, and vice versa.

    Full Answer >
    Filed Under:

Explore