interpolation
Both, interpolation and extrapolation are used to predict, or estimate, the value of one variable when the value (or values) of other variable (or variables) is known. This is done by extending evaluating the underlying function. For interpolation, the point in question is within the domain of the observed values (there are observations for greater and for smaller values of the variables) wheres for extrapolation the point in question is outside the domain.
a estimate is based on known information it is just not a true answer.
Classical approach has possible outcomes which are known with certainity ie sampling distribution is known. Relative approach is an approach in which probability values are based on historical interest.
This is the Arithmetic Mean (also known as the average).
For data sets having a normal distribution, the following properties depend on the mean and the standard deviation. This is known as the Empirical rule. About 68% of all values fall within 1 standard deviation of the mean About 95% of all values fall within 2 standard deviation of the mean About 99.7% of all values fall within 3 standard deviation of the mean. So given any value and given the mean and standard deviation, one can say right away where that value is compared to 60, 95 and 99 percent of the other values. The mean of the any distribution is a measure of centrality, but in case of the normal distribution, it is equal to the mode and median of the distribtion. The standard deviation is a measure of data dispersion or variability. In the case of the normal distribution, the mean and the standard deviation are the two parameters of the distribution, therefore they completely define the distribution. See: http://en.wikipedia.org/wiki/Normal_distribution
It is called extrapolation.
It is called EXTRAPOLATION and should only be used with great care.
If you know the two values you shouldn't have to estimate. But you are looking for the mean, or average. Simply add them together and divide by two. Otherwise you are just estimating.
It means to decide what the next thing would be based on the things you already know. For example, if you had a linear equation (a graph where the line is completely straight) and you knew three points, you would be able to use the three points (the known values) to figure out what the fourth or fifth points (the value you are estimating) would be based on the space between each point (the given data).It is called extrapolation (or forecasting) and is usually subject to quite large errors.
to estimate the parameter values of a known distribution like normal distribution in this we estimate the parameters pop.mean and s.d
Interpolation
In order to give an accurate estimate of value of any coin the date on the coin must be known.
Both, interpolation and extrapolation are used to predict, or estimate, the value of one variable when the value (or values) of other variable (or variables) is known. This is done by extending evaluating the underlying function. For interpolation, the point in question is within the domain of the observed values (there are observations for greater and for smaller values of the variables) wheres for extrapolation the point in question is outside the domain.
BHARGAV is not a known english term and you have asked what is the difference. The difference between what & what would have to be know terms/ values.
a estimate is based on known information it is just not a true answer.
Amps are coulombs per second, and there is no information on rates given here.
Tallest is when its known defiant that size is different taller is just a persons self estimate