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The expected size of each group is 500. However, the actual sizes of the treatment and control groups are 600 and 400. Using Pearson's chi-squared goodness of fit test, we find a sample ratio mismatch with a p -value of 2.54 × 10 -10 .
The actual difference is not usually a good way to compare the numbers, in particular because it depends on the unit of measurement. For instance, 1 m is the same as 100 cm, but the absolute difference between 2 and 1 m is 1 while the absolute difference between 200 and 100 cm is 100, giving the impression of a larger difference. [4]
This consists in first calculating the difference between the expected and actual performances (the best fit line previously identified and the points themselves). The CUSUM can then be plotted against time on a new graph, which then yields more information for the energy efficiency specialist.
Price variance (Vmp) is a term used in cost accounting which denotes the difference between the expected cost of an item (standard cost) and the actual cost at the time of purchase. [1] The price of an item is often affected by the quantity of items ordered, and this is taken into consideration.
In accounting parlance, margin of safety is the difference between the expected (or actual) sales level and the breakeven sales level. It can be expressed in the equation form as follows: Margin of Safety = Expected (or) Actual Sales Level (quantity or dollar amount) - Breakeven sales Level (quantity or dollar amount)
A typical measure of bias of forecasting procedure is the arithmetic mean or expected value of the forecast errors, but other measures of bias are possible. For example, a median-unbiased forecast would be one where half of the forecasts are too low and half too high: see Bias of an estimator .
If the expected value exists, this procedure estimates the true expected value in an unbiased manner and has the property of minimizing the sum of the squares of the residuals (the sum of the squared differences between the observations and the estimate).
Forecasting is the process of making predictions based on past and present data. Later these can be compared with what actually happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results creating a variance actual analysis.