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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.
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.
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.
The company's operating income margin or return on sales (ROS) is (EBIT ÷ Revenue). This is the operating income per dollar of sales. [EBIT/Revenue] The company's asset turnover (ATO) is (Revenue ÷ Average Total Assets). The company's equity multiplier is (Average Total Assets ÷ Average Total Equity). This is a measure of financial leverage.
where R 2 is the coefficient of determination and VAR err and VAR tot are the variance of the residuals and the sample variance of the dependent variable. SS err (the sum of squared predictions errors, equivalently the residual sum of squares ), SS tot (the total sum of squares ), and SS reg (the sum of squares of the regression, equivalently ...
The constraint on production of the railcoaches was the metalwork shop. She made an analysis of profit and loss if the company took the contract using throughput accounting to determine the profitability of products by calculating "throughput" (revenue less variable cost) in the metal shop.
Let a be the value of our statistic as calculated from the full sample; let a i (i = 1,...,n) be the corresponding statistics calculated for the half-samples.(n is the number of half-samples.)
This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line.. Because SumSq and (Sum×Sum)/n can be very similar numbers, cancellation can lead to the precision of the result to be much less than the inherent precision of the floating-point arithmetic used to perform the computation.