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There are two reasons actual sales can vary from planned sales: either the volume sold varied from the expected quantity, known as sales volume variance, or the price point at which units were sold differed from the expected price points, known as sales price variance. Both scenarios could also simultaneously contribute to the variance.
More recently, the term "multi-vari chart" has been used to describe a visual way to display analysis of variance data (typically be expressed in tabular format). [5] It consists of a series of panels which portray minimum, mean, and maximum responses for each treatment combination of interest rather than for periods of time.
Variance analysis can be carried out for both costs and revenues. Variance analysis is usually associated with explaining the difference (or variance) between actual costs and the standard costs allowed for the good output. For example, the difference in materials costs can be divided into a materials price variance and a materials usage variance.
For example, if time progresses left to right, traditional retailers have focused on the area to the left of the chart, while online bookstores derive more sales from the area to the right. The long tail is the name for a long-known feature of some statistical distributions (such as Zipf , power laws , Pareto distributions and general Lévy ...
"The scatter chart below shows the r-squared between the two, which is 0.0. ... which explains the variance in equity returns attributed to the level of concentration, is negligible, at 0.04% ...
It says what fraction of the variance of the data is explained by the fitted trend line. It does not relate to the statistical significance of the trend line (see graph); the statistical significance of the trend is determined by its t-statistic. Often, filtering a series increases r 2 while making little difference to the fitted trend.
Often, variation is quantified as variance; then, the more specific term explained variance can be used. The complementary part of the total variation is called unexplained or residual variation ; likewise, when discussing variance as such, this is referred to as unexplained or residual variance .
The graphs can be used together to determine the economic equilibrium (essentially, to solve an equation). Simple graph used for reading values: the bell-shaped normal or Gaussian probability distribution, from which, for example, the probability of a man's height being in a specified range can be derived, given data for the adult male population.