a ( n ) is a difference between actual and budgeted performance
variance
4193163
is determined by the needs of users of the variance information and may include e.g.: Let us assume that standard direct material cost of production is as follows: Let us assume further that during the given period, 200 units of fuselage were manufactured, using X kg of Kevlar which cost Y Direct material total variance can be calculated as Variance (accounting) In budgeting (or management accounting in general), a variance is the difference between a budgeted, planned, or standard cost and the actual amount incurred/sold. Variances can be computed for both costs and revenues. The concept of variance is intrinsically
Variance (accounting)
4193162
Variance (accounting) In budgeting (or management accounting in general), a variance is the difference between a budgeted, planned, or standard cost and the actual amount incurred/sold. Variances can be computed for both costs and revenues. The concept of variance is intrinsically connected with planned and actual results and effects of the difference between those two on the performance of the entity or company. Variances can be divided according to their effect or nature of the underlying amounts. When effect of variance is concerned, there are two types of variances: The second typology (according to the nature of the underlying amount)
Variance (accounting)
12785799
of the difference, managers need to investigate the questions how the variance differs from last period and what are the causes for not reaching the estimated figures. Analysers consider two types of variances: adverse variance and favourable variance. Adverse variance “exists when the difference between the budgeted and actual figure leads to a lower than expected profit”. Favourable variance “exists when the difference between the budgeted and actual figure leads to a higher than expected profit”. Rather than considering all variances, managers establish criteria to determine which variances are significant to focus on. Management by exception focuses mainly on large
Management by exception
10074876
Sales variance Sales variance is the difference between actual sales and budget sales. It is used to measure the performance of a sales function, and/or analyze business results to better understand market conditions. There are two reasons actual sales can vary from planned sales: either the volume sold varied from plan (sales volume variance), or sales were at a different price from what was planned (sales price variance). Both scenarios could also simultaneously contribute to the variance. For example: The plan was to sell 5 widgets at $3 each, for a budgeted sales of: (5*$3)=$15. In reality, 6 widgets were
Sales variance
4258559
Direct material total variance In variance analysis (accounting) direct material total variance is the difference between the actual cost of actual number of units produced and its budgeted cost in terms of material. Direct material total variance can be divided into two components: Let us assume that standard direct material cost of widget is as follows: Let us assume further that during the given period, 100 widgets were manufactured, using 212 kg of unobtainium which cost $ 13,144. Under those assumptions direct material total variance can be calculated as: Direct material total variance can be reconciled to direct material price
Direct material total variance
4258560
variance and direct material usage variance by: See direct material usage variance#Example and direct material price variance#Example for computations of both components. Direct material total variance In variance analysis (accounting) direct material total variance is the difference between the actual cost of actual number of units produced and its budgeted cost in terms of material. Direct material total variance can be divided into two components: Let us assume that standard direct material cost of widget is as follows: Let us assume further that during the given period, 100 widgets were manufactured, using 212 kg of unobtainium which cost $ 13,144.
Direct material total variance
4193163
is determined by the needs of users of the variance information and may include e.g.: Let us assume that standard direct material cost of production is as follows: Let us assume further that during the given period, 200 units of fuselage were manufactured, using X kg of Kevlar which cost Y Direct material total variance can be calculated as Variance (accounting) In budgeting (or management accounting in general), a variance is the difference between a budgeted, planned, or standard cost and the actual amount incurred/sold. Variances can be computed for both costs and revenues. The concept of variance is intrinsically
Variance (accounting)
15975084
the variance, the larger the standard deviation, the more uncertain the outcome. The standard deviation, E is a measure of average difference between the expected value and the actual value of a random variable (or unseen state of nature). Here, n stands for a possible outcome, x stands for the expected outcome and P is the probability (or likelihood) of the difference between n and X occurring. The term Risk and the types associated to it would refer to mean financial risk or uncertainty of financial loss. The Reserve Bank of India guidelines issued in Oct. 1999 has identified and
Risk management in Indian banks
10074877
sold at $2 each, for an actual sales of: (6*$2)=$12. The total variance was thus ($12–$15)=$3 (U)nfavourable or minus $3, since total sales was less than planned. Sales Price Variance: The sales price variance reveals the difference in total revenue caused by charging a different selling price from the planned or standard price. The sales price variance is calculated as: Actual quantity sold * (actual selling price - planned selling price). In the example, the sales price variance was 6*($2–$3)= -$6 (U)nfavourable or minus $6, since the sales price was less than planned. Sales Volume Variance is calculated as: budgeted
Sales variance
12785798
or norms with predictable or estimated results. These performances are assessed and get equated to the actual performance. Next, the deviation gets analysed. With an insignificant or no deviation, no action is required and senior managers can concentrate on other matters. If actual performances deviate significantly, the concern needs to be passed to the senior managers, as an “exception has occurred”. Finally, the aim is to solve this “exception” immediately. The accounting department is responsible for the forecasting of budgets and cost performance reports. The difference between the estimated and actual figures is defined as variance. To understand the cause
Management by exception
5004364
Direct labour cost variance Direct labour cost variance is the difference between the standard cost for actual production and the actual cost in production. There are two kinds of labour variances. "Labour Rate Variance" is the difference between the standard cost and the actual cost paid for the actual number of hours. "Labour efficiency variance" is the difference between the standard labour hour that should have been worked for the actual number of units produced and the actual number of hours worked when the labour hours are valued at the standard rate. Difference between the amount of labor time that
Direct labour cost variance
5004366
x 2000 units of output. This variance is favorable since the actual hours used are less than the standard hours allowed. This may be the result of efficient use of labor time due to automation or the use of improved production methods. Direct labour cost variance Direct labour cost variance is the difference between the standard cost for actual production and the actual cost in production. There are two kinds of labour variances. "Labour Rate Variance" is the difference between the standard cost and the actual cost paid for the actual number of hours. "Labour efficiency variance" is the difference
Direct labour cost variance
16667205
formula_17 being simultaneously correct is equal to a specified value,formula_20. When calculating one sided upper (or lower) Confidence interval for the true value of the difference between the mean of the treatment and the control group, formula_20 constitutes the probability that this actual value will be less than the upper (or greater than the lower) limit of that interval. When calculating two-sided confidence interval, formula_20 constitutes the probability that the true value will be between the upper and the lower limits. First, we will denote the available N observations by formula_23 when formula_24 and formula_25 and estimate the common variance
Dunnett's test
12614962
approach to Project management. BCWP is contrasted to Budgeted Cost for Work Scheduled (BCWS) also called Planned Value (PV). BCWS is the sum of the budget items for all work packages, planning packages, and overhead which was scheduled for the period, rather than the cost of the work actually performed. BCWP is also contrasted to Actual Cost of Work Performed (ACWP) which measures the actual amount spent rather than the budgeted estimates. To illustrate the difference between the three terms, assume that a schedule contains a task "Test hardware" estimated to run from 1 January to 10 January and to
Budgeted cost of work performed
15788409
there is an implied triangle "ACD", with one side given ("AC" = 70 miles on actual NW course), a 45° angle at "A" (angle of difference between actual course NW and intended course N) and another angle of 90° at "C" (angle of difference between actual course NW and return course NE). The challenge to the navigator is to find how long one must sail on the NE return course (the length of side "CD", what is called the "ritorno") and how far one has advanced on the intended course by the time one straightens out (the length of the
Rule of marteloio
6573562
further assumption is that the exhaust gases would be passed from the exhaust to a heat exchanger that would sink the waste heat to the environment and the working gas would be reused at the inlet stage. The difference between an idealized cycle and actual performance may be significant. For example, the following images illustrate the differences in work output predicted by an ideal Stirling cycle and the actual performance of a Stirling engine: As the net work output for a cycle is represented by the interior of the cycle, there is a significant difference between the predicted work output
Thermodynamic cycle
122581
To measure cost performance, planned value (or BCWS - Budgeted Cost of Work Scheduled) and earned value (or BCWP - Budgeted Cost of Work Performed) must be in units of currency (the same units that actual costs are measured.) In large implementations, the planned value curve is commonly called a Performance Measurement Baseline (PMB) and may be arranged in control accounts, summary-level planning packages, planning packages and work packages. In large projects, establishing control accounts is the primary method of delegating responsibility and authority to various parts of the performing organization. Control accounts are cells of a responsibility assignment (RACI)
Earned value management
17424900
projects. Nigeria Sovereign Investment Authority The Nigeria Sovereign Investment Authority is a Nigerian establishment which manages the "Nigeria sovereign wealth fund", into which the surplus income produced from Nigeria's excess oil reserves is deposited. This sovereign wealth fund was founded for the purpose of managing and investing these funds on behalf of the government of Nigeria. The wealth fund commenced operations in October 2012 and was set up by the Nigeria Sovereign Investment Authority Act, which was signed in May 2011. It is intended to invest the savings gained on the difference between the budgeted and actual market prices for
Nigeria Sovereign Investment Authority
17424893
Nigeria Sovereign Investment Authority The Nigeria Sovereign Investment Authority is a Nigerian establishment which manages the "Nigeria sovereign wealth fund", into which the surplus income produced from Nigeria's excess oil reserves is deposited. This sovereign wealth fund was founded for the purpose of managing and investing these funds on behalf of the government of Nigeria. The wealth fund commenced operations in October 2012 and was set up by the Nigeria Sovereign Investment Authority Act, which was signed in May 2011. It is intended to invest the savings gained on the difference between the budgeted and actual market prices for oil
Nigeria Sovereign Investment Authority
518131
medical error for a description of error in medicine. In statistics, an error (or "residual") is not a "mistake" but rather a difference between a computed, estimated, or measured value and the accepted true, specified, or theoretically correct value. In science and engineering in general an error is defined as a difference between the desired and actual performance or behavior of a system or object. This definition is the basis of operation for many types of control systems, in which error is defined as the difference between a set point and the process value. An example of this would be
Error
5883309
of probabilistic predictions, or as a "cost function". More precisely, across all items formula_1 in a set "N" predictions, the Brier score measures the mean squared difference between: Therefore, the lower the Brier score is for a set of predictions, the better the predictions are calibrated. Note that the Brier score, in its most common formulation, takes on a value between zero and one, since this is the largest possible difference between a predicted probability (which must be between zero and one) and the actual outcome (which can take on values of only 0 or 1). In the original (1950)
Brier score
8258190
is attempting to standardize the delivery of education and lower costs. For fiscal year 2011/2012, which began 1 July 2011, the education sector national budget is 2,283 billion Tanzanian shillings, which equates to US$1.45 billion (at an exchange rate of 1,591 shillings per dollar). This is an 11.6% increase over the amount budgeted for fiscal year 2010/2011. After accounting for inflation, however, the increase is approximately 1%. Based on actual performance in recent fiscal years, the amount budgeted for the Tanzanian Ministry of Education and Vocational Training is typically much more than the amount spent. In fiscal year 2008/2009, the
Education in Tanzania
9268301
mimic a desired filter by finding the filter coefficients that relate to producing the least mean square of the error signal (difference between the desired and the actual signal). For example, stable partition, using no additional memory is "O"("n" lg "n") but given "O"("n") memory, it can be "O"("n") in time. As implemented by the C++ Standard Library, codice_1 is adaptive and so it acquires as much memory as it can get (up to what it would need at most) and applies the algorithm using that available memory. Another example is adaptive sort, whose behavior changes upon the presortedness of
Adaptive algorithm
7017600
home of" (cf. French "chez", German "bei"). Note 2: "-ban/-ben" is sometimes pronounced without the final "n", this however, carries a connotation of rural or unsophisticated speech. For town/city names, the rules for selecting the right group are as follows: The difference of the two suffix group may carry a difference in meaning: The below cases may exemplify the above tendencies but in actual usage they are not always followed as strictly as described: There may also be difference between "insider" and "outsider" usage: one may prefer the suffixes expressing the "interior" relation and the others those expressing the "surface"
Hungarian noun phrase
2911487
closest perfect square to the desired square "x" and "d" = "x" - "n" is their difference, it is more convenient to express this approximation in the form of mixed fraction as formula_39. Thus, in the previous example, the square root of 15 is formula_40 As another example, square root of 41 is formula_41 while the actual value is 6.4031... By definition, if "r" is the square root of x, then We then redefine the root where "a" is a known root (4 from the above example) and "b" is the difference between the known root and the answer we
Mental calculation
13782172
Symmetric mean absolute percentage error Symmetric mean absolute percentage error (SMAPE or sMAPE) is an accuracy measure based on percentage (or relative) errors. It is usually defined as follows: where "A" is the actual value and "F" is the forecast value. The absolute difference between "A" and "F" is divided by half the sum of absolute values of the actual value "A" and the forecast value "F". The value of this calculation is summed for every fitted point "t" and divided again by the number of fitted points "n". The earliest reference to similar formula appears to be Armstrong (1985,
Symmetric mean absolute percentage error
8093369
in conjunction with a comparator internal to the DAC and the successive approximation register. When implemented as an analog circuit – where the value of each successive bit is not perfectly 2 (e.g. 1.1, 2.12, 4.05, 8.01, etc.) – a successive approximation approach might not output the ideal value because the binary search algorithm incorrectly removes what it believes to be half of the values the unknown input cannot be. Depending on the difference between actual and ideal performance, the maximum error can easily exceed several LSBs, especially as the error between the actual and ideal 2becomes large for one
Successive approximation ADC
14498726
equipped with a function formula_1, receives "n" real-valued inputs formula_2 with respective weights formula_3, and it outputs formula_4. Some neurons are selected to be the output neurons, and the network function is the vectorial function that associates to the "n" input values, the outputs of the "m" selected output neurons. Note that different choices of weights produce different network functions for the same inputs. Back-propagation is a supervised learning method by which the weights of the connections in the network are repeatedly adjusted so as to minimize the difference between the vector of actual outputs and that of desired outputs.
Natural computing
15788454
the known information given is the "actual course" and the "ritorno", while the unknowns are the "intended bearing" and "total avanzo". Traverse tables use three values for each of the crooked course segments – the "Distance" (Dist.), "Difference of Latitude" (D.Lat., movement along N–S axis) and the "Departure" (Dep., movement along E–W axis), the latter two calculated by the formulas: where "θ" is the angular difference of the course from the N–S axis if the values of "θ" are less than 45°; if, however, the angle exceeds 45°, then "θ" is expressed as the angle of difference from the E–W
Rule of marteloio
20557113
context of a research project of the University of Zurich under the direction of Ernst Fehr, the MAPI was developed and implemented with the consultancy firm Fehr Advice & Partners. To do this, a listed company’s total shareholder return (TSR) is compared with the TSR of a customised, relevant peer group. This way external market shocks, for which the management should be neither rewarded nor penalised, can be excluded. The difference between the TSR of the company and that of its peer group provides insights into the actual performance of the CEO and top management. This makes management performance transparent.
Market-Adjusted Performance Indicator
18930955
indicates the amount of fuel required to generate one unit of electricity. Performance parameters tracked for any thermal power plant like efficiency, fuel costs, plant load factor, emissions level, etc. are a function of the station heat rate and can be linked directly. Given that heat rate and efficiency are inversely related to each other, it is possible to convert from one to the other: Most power plants have a target or design heat rate. If the actual heat rate does not match the target, the difference between the actual and target heat rate is the heat rate deviation. Heat
Heat rate (efficiency)
20419028
formula_32 is improved iteratively by calculating the difference between the actual focal stack formula_31 and the estimated focal stack formula_42 and correcting formula_32 with the current difference (formula_32 is constrained to be non-negative). Although ray-optics based plenoptic camera has demonstrated favorable performance in the macroscopic world, diffraction places a limit on the LFM reconstruction when staying with ray-optics parlance. Hence, it may be much more convenient to switch to wave optics. (This section mainly introduce the work of Broxton "et al"., 2013.) The interested FOV is segmented into formula_45 voxels, each with a label formula_46. Thus, the whole FOV can
Light field microscopy
6164796
Gap analysis In management literature, gap analysis involves the comparison of actual performance with potential or desired performance. If an organization does not make the best use of current resources, or forgoes investment in capital or technology, it may produce or perform below an idealized potential. This concept is similar to an economy's production being below the production possibilities frontier. Gap analysis identifies gaps between the optimized allocation and integration of the inputs (resources), and the current allocation-level. This may reveal areas that can be improved. Gap analysis involves determining, documenting, and improving the difference between business requirements and current
Gap analysis
12696721
size 120, 30mm venturi, with K&N performance filters. The maximum power was 100 bhp at 6000 rpm. They ran on list 1A Michelin MXT tyres. In 1998, the engine supplier changed to Vauxhall, with 1600 single overhead cam engines being used. They featured a ported & skimmed cylinder head, standard Vauxhall camshaft, flywheel and clutch cover plate, two Weber twin choke 40 DCOE 151 (sidedraft) carburettors, main jets size 115, with K&N performance filters. The maximum power was 101 ps at 5,500 rpm and a max torque of 107 lb ft at 3,600 rpm. The main visual difference between the
Caterham Academy
7260807
the industry whether the small difference in yearly collection between single and dual-axis trackers makes the added complexity of a two-axis tracker worthwhile. A recent review of actual production statistics from southern Ontario suggested the difference was about 4% in total, which was far less than the added costs of the dual-axis systems. This compares unfavourably with the 24-32% improvement between a fixed-array and single-axis tracker. The above models assume uniform likelihood of cloud cover at different times of day or year. In different climate zones cloud cover can vary with seasons, affecting the averaged performance figures described above. Alternatively,
Solar tracker
11434639
under unitary transformations whereas the Gaussian orthogonal ensemble (GOE) consists of real symmetric matrices invariant under orthogonal transformations. The ranked eigenvalues "E" from these random matrices obey Wigner’s semicircular distribution: For a "N"×"N" matrix the average density for eigenvalues of size "E" will be as "E". Integration of the semicircular rule provides the number of eigenvalues on average less than "E", The ranked eigenvalues can be unfolded, or renormalized, with the equation This removes the trend of the sequence from the fluctuating portion. If we look at the absolute value of the difference between the actual and expected cumulative number
Tweedie distribution
7982744
(9 weeks) for "n" = 2, 3, 4, 5, and 6, i.e., between 4/4, 6/6, 8/8, 10/10, and 12/12. For "m" = 2"n" + 1 and "d"="m" + 4 we get and with "m" and "d" interchanged giving a difference of 119 (17 weeks) for "n" = 2 (difference between 5/9 and 9/5), and also for "n" = 3 (difference between 7/11 and 11/7). The ordinal date from 1 January is: or equivalently, the ordinal date from 1 March of the previous year (for which the formula above can be used) minus 306. Again counting January and February as month
Ordinal date
519378
In organizational development (OD), "performance" can be thought of as Actual Results vs Desired Results. Any discrepancy, where Actual is less than Desired, could constitute the performance improvement zone. Performance management and improvement can be thought of as a cycle: A performance problem is any gap between Desired Results and Actual Results. Performance improvement is any effort targeted at closing the gap between Actual Results and Desired Results. Other organizational development definitions are slightly different. The U.S. Office of Personnel Management (OPM) indicates that Performance Management consists of a system or process whereby: Many people equate performance management with performance
Performance management
14613015
Matrix difference equation A matrix difference equation is a difference equation in which the value of a vector (or sometimes, a matrix) of variables at one point in time is related to its own value at one or more previous points in time, using matrices. The order of the equation is the maximum time gap between any two indicated values of the variable vector. For example, is an example of a second-order matrix difference equation, in which "x" is an "n" × 1 vector of variables and "A" and "B" are "n×n" matrices. This equation is homogeneous because there is
Matrix difference equation
14613005
Matrix difference equation A matrix difference equation is a difference equation in which the value of a vector (or sometimes, a matrix) of variables at one point in time is related to its own value at one or more previous points in time, using matrices. The order of the equation is the maximum time gap between any two indicated values of the variable vector. For example, is an example of a second-order matrix difference equation, in which "x" is an "n" × 1 vector of variables and "A" and "B" are "n×n" matrices. This equation is homogeneous because there is
Matrix difference equation
19197674
Invisible Lost Time Invisible Lost Time (ILT) related to routine rig drilling operations is the difference between actual operational duration and a best practice target. It is invisible because it does not appear on any conventional morning reports. The measurement of Invisible Lost Time starts by analyzing each individual key performance indicator (KPI) that can be produced by a particular crew (drilling crew, casing crew, etc.), by a machine-automated operation, or a combination of both. The measurement of Invisible Lost Time was first developed and used by Statoil and TDE. Source: Case History: Automated Drilling Performance Measurement of Crews and
Invisible Lost Time
16521849
"Hang(Node n, Element e)" The main difference between the kinetic hanger and the kinetic heap is in the key operations, which are implemented as follows in a kinetic hanger: All these operations result in a uniformly random structure for the hanger, with an expected height of O(log n). This structure is: Kinetic hanger A Kinetic hanger is a randomized version of a kinetic heap whose performance is easy to analyze tightly. A kinetic hanger satisfies the heap property (the priority of each element is higher than the priority of its children) but relaxes the requirement that the tree structure must
Kinetic hanger
1701244
defined time periods. In the case of a contract for difference, if a resulting wholesale price index (as referenced in the contract) in any time period is higher than the "strike" price, the generator will refund the difference between the "strike" price and the actual price for that period. Similarly a retailer will refund the difference to the generator when the actual price is less than the "strike price". The actual price index is sometimes referred to as the "spot" or "pool" price, depending on the market. Many other hedging arrangements, such as swing contracts, virtual bidding, Financial Transmission Rights,
Electricity market
2900398
problem instance "x") is: That is to say that formula_11 is the largest bound on the approximation ratio, "r", that one sees over all possible instances of the problem. Likewise, the "asymptotic performance ratio" formula_15 is: That is to say that it is the same as the "absolute performance ratio", with a lower bound "n" on the size of problem instances. These two types of ratios are used because there exist algorithms where the difference between these two is significant. In the literature, an approximation ratio for a maximization (minimization) problem of "c" - ϵ (min: "c" + ϵ) means
Approximation algorithm
12836844
private, whereas the actual rainbow is "shared". He is careful to point out, however, that being shared is not the only difference between an actual rainbow and a dream of one. An actual phenomenon is not merely a dream that is shared. Even if one is alone on a desert island, one can learn from the world itself the difference between appearances that are actually there, and appearances that are there only in the manner of hallucinations. Barfield argues that three components make up an appearance, say, of a real tree: (1) the "unrepresented," namely that which is supposed to
Saving the Appearances: A Study in Idolatry
6671443
difference between the 2"n"-th Mersenne number and the "n"-th Carol number is formula_4. This gives yet another equivalent expression for Carol numbers, formula_5. The difference between the "n"-th Kynea number and the "n"-th Carol number is the ("n" + 2)th power of two. Starting with 7, every third Carol number is a multiple of 7. Thus, for a Carol number to also be a prime number, its index "n" cannot be of the form 3"x" + 2 for "x" > 0. The first few Carol numbers that are also prime are 7, 47, 223, 3967, 16127 (these are listed in
Carol number
4153263
state or time step and the actual reward received. The larger the error function, the larger the difference between the expected and actual reward. When this is paired with a stimulus that accurately reflects a future reward, the error can be used to associate the stimulus with the future reward. Dopamine cells appear to behave in a similar manner. In one experiment measurements of dopamine cells were made while training a monkey to associate a stimulus with the reward of juice. Initially the dopamine cells increased firing rates when the monkey received juice, indicating a difference in expected and actual
Temporal difference learning
2335924
rather common situations. For example, when the items are inserted in sorted key order, the tree degenerates into a linked list with "n" nodes. The difference in performance between the two situations may be enormous: for "n" = 1,000,000, for example, the minimum height is formula_4. If the data items are known ahead of time, the height can be kept small, in the average sense, by adding values in a random order, resulting in a random binary search tree. However, there are many situations (such as online algorithms) where this randomization is not viable. Self-balancing binary trees solve this problem
Self-balancing binary search tree
9201306
that no more than 25 trials be performed, as listener fatigue can set in, making the test less sensitive (less likely to reveal one's actual ability to discern the difference between A and B). However, a more sensitive test can be obtained by pooling the results from a number of such tests using separate individuals or tests from the same listener conducted in between rest breaks. For a large number of total trials N, a significant result (one with 95% confidence) can be claimed if the number of correct responses exceeds formula_1. Important decisions are normally based on a higher
ABX test
6667653
test is often used as a genotype-based test for case-control genetic association studies. The trend test is applied when the data take the form of a 2 × "k" contingency table. For example, if "k" = 3 we have This table can be completed with the marginal totals of the two variables where "R" = "N" + "N" + "N", and "C" = "N" + "N", etc. The trend test statistic is where the "t" are weights, and the difference "N""R" −"N""R" can be seen as the difference between "N" and "N" after reweighting the rows to have the same
Cochran–Armitage test for trend
4544647
Abnormal return In finance, an abnormal return is the difference between the actual return of a security and the expected return. Abnormal returns are sometimes triggered by "events." Events can include mergers, dividend announcements, company earning announcements, interest rate increases, lawsuits, etc. all of which can contribute to an abnormal return. Events in finance can typically be classified as information or occurrences that have not already been priced by the market. In stock market trading, abnormal returns are the differences between a single stock or portfolio's performance and the expected return over a set period of time. Usually a broad
Abnormal return
16697068
particular, what is the smallest possible difference between the areas of the smallest and largest triangles? Let the smallest difference be "M"("n") for a square and "M"("a", "n") for the trapezoid "T"("a"). Then "M"("n") is 0 for even "n" and greater than 0 for odd "n". gave the asymptotic upper bound "M"("n") = O(1/"n") (see Big O notation). improves the bound to "M"("n") = O(1/"n") with a better dissection, and he proves that there exist values of "a" for which "M"("a", "n") decreases arbitrarily quickly. obtain a superpolynomial upper bound, derived from an explicit construction that uses the Thue–Morse sequence.
Equidissection
9372756
both absorption and emission. The performance of a layer stack can be quantified in terms of its overall heat transfer coefficient "U", which defines the radiative heat flow rate "Q" between two parallel surfaces with a temperature difference formula_1 and area "A" as Theoretically, the heat transfer coefficient between two layers with emissivities formula_3 and formula_4, under vacuum, is where "T" is the mean of the temperatures (in K) of the two layers and formula_6 WmK is the Stefan-Boltzmann Constant. If each layer has the same emissivity formula_7 on both sides, then a stack of "N" layers placed between two
Multi-layer insulation
19650321
5 and 6 in the shot put. It found there was little significant difference in performance in time between men in 4, 5 and 6 in the 100 meters. It found there was little significant difference in performance in time between men in 4, 5 and 6 in the 800 meters. It found there was little significant difference in performance in time between men in 4, 5 and 6 in the 1,500 meters. It found there was little significant difference in performance in time between men in 4, 5 and 6 in the slalom. Rowing is one of the sports
F5 (classification)
19650354
difference in performance in distance between women in 4, 5 and 6 in the shot put. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the discus. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 60 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 800 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in
F6 (classification)
19650215
difference in performance in distance between men in 1A and 1B in the javelin. It found there was little significant difference in performance in distance between men in 1A and 1B in the shot put. It found there was little significant difference in performance in times between women in 1A and 1B in the 60 meters. It found there was little significant difference in performance in times between men in 1A and 1B in the 60 meters. It found there was little significant difference in performance in times between women in 1A and 1B in the slalom. It found there
F2 (classification)
19637795
there was little significant difference in performance in distance between women in 5 and 6 in the discus. It found there was little significant difference in performance in time between women in 5 and 6 in the 60 meters. It found there was little significant difference in performance in time between women in 5 and 6 in the 100 meters. It found there was little significant difference in performance in distance between men in 5 and 6 in the javelin. It found there was little significant difference in performance in distance between men in 5 and 6 in the shot
F56 (classification)
19637792
was little significant difference in performance in distance between women in 4, 5 and 6 in the discus. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the javelin. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the shot put. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the discus. It found there was little significant difference in performance in time between women in 4, 5 and 6
F56 (classification)
19637767
found there was little significant difference in performance in distance between women in 5 and 6 in the discus. It found there was little significant difference in performance in time between women in 5 and 6 in the 60 meters. It found there was little significant difference in performance in time between women in 5 and 6 in the 100 meters. It found there was little significant difference in performance in distance between men in 5 and 6 in the javelin. It found there was little significant difference in performance in distance between men in 5 and 6 in the
F57 (classification)
19637764
was little significant difference in performance in distance between women in 4, 5 and 6 in the discus. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the javelin. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the shot put. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the discus. It found there was little significant difference in performance in time between women in 4, 5 and 6
F57 (classification)
16086501
significant difference in performance in distance between women in 1A (SP1, SP2) and 1B (SP3) in the club throw. It found there was little significant difference in performance in distance between men in 1A and 1B in the club throw. It found there was little significant difference in performance in distance between men in 1A and 1B in the discus. It found there was little significant difference in performance in distance between men in 1A and 1B in the javelin. It found there was little significant difference in performance in distance between men in 1A and 1B in the shot
T52 (classification)
16075203
little significant difference in performance times between women in 1A (SP1, SP2), 1B (SP3), and 1C (SP3, SP4) in the 25m breaststroke. It found there was little significant difference in performance times between women in 1A, and 1C in the 25m backstroke. It found there was little significant difference in performance times between women in 1A, 1B, and 1C in the 25m freestyle. It found there was little significant difference in performance times between men in 1A, 1B, and 1C in the 25m backstroke. It found there was little significant difference in performance times between men in 1A, 1B, and
S4 (classification)
16075159
difference in performance times between women in 2 and 3 in the 50m breaststroke. It found there was little significant difference in performance times between men in 2 (SP4) and 3 (SP4, SP5) in the 50m breaststroke. It found there was little significant difference in performance times between women in 2 (SP4) and 3 (SP4, SP5) in the 50m freestyle. It found there was little significant difference in performance times between men in 2 and 3 in the 50m freestyle. It found there was little significant difference in performance times between men in 2 (SP4) and 3 (SP4, SP5) in
S5 (classification)
16075237
difference in performance times between men in 2 and 3 in the 50m freestyle. It found there was little significant difference in performance times between men in 2 (SP4) and 3 (SP4, SP5) in the 50m backstroke. It found there was little significant difference in performance times between women in 2, 3 and 4 in the 25 m butterfly. It found there was little significant difference in performance times between men in 2, 3 and 4 in the 25 m butterfly. This is wheelchair sport classification that corresponds to the neurological level T8 - L1. In the past, this class
S3 (classification)
19650385
there was little significant difference in performance in distance between women in 4, 5 and 6 in the shot put. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the discus. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 60 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 800 meters. It found there was little significant difference in performance in time between women in 4,
F7 (classification)
19650355
the 1,500 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the slalom. It found there was little significant difference in performance in distance between men in 4, 5 and 6in the discus. It found there was little significant difference in performance in distance between men in 4, 5 and 6 in the shot put. It found there was little significant difference in performance in time between men in 4, 5 and 6 in the 100 meters. It found there was little significant difference in performance in time between
F6 (classification)
19650320
found there was little significant difference in performance in time between women in 4, 5 and 6 in the 800 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 1,500 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the slalom. It found there was little significant difference in performance in distance between men in 4, 5 and 6 in the discus. It found there was little significant difference in performance in distance between men in 4,
F5 (classification)
19650317
significant difference in performance in time between men in 2 (SP4) and 3 in the 200 meters. It found there was little significant difference in performance in time between men in 2 (SP4) and 3 in the 400 meters. It found there was little significant difference in performance in distance between women in 2 (SP4), 3 and 4 in the discus. It found there was little significant difference in performance in time between men in 2 (SP4), 3 and 4 in the 100 meters. It found there was little significant difference in performance in distance between women in 2 (SP4),
F5 (classification)
19650315
It found there was little significant difference in performance in distance between women in 2 (SP4) and 3 in the shot put. It found there was little significant difference in performance in time between women in 2 (SP4) and 3 in the 60 meters. It found there was little significant difference in performance in time between women in 2 (SP4) and 3 in the 200 meters. It found there was little significant difference in performance in time between women in 2 (SP4) and 3 in the 400 meters. It found there was little significant difference in performance in time between
F5 (classification)
19650290
25m freestyle. It found there was little significant difference in performance times between women in 2 and 3 in the 50m breaststroke. It found there was little significant difference in performance times between men in 2 (SP4) and 3 (SP4, SP5) in the 50m breaststroke. It found there was little significant difference in performance times between women in 2 (SP4) and 3 (SP4, SP5) in the 50m freestyle. It found there was little significant difference in performance times between men in 2 and 3 in the 50m freestyle. It found there was little significant difference in performance times between men
F4 (classification)
19637822
was little significant difference in performance in distance between women in 4, 5 and 6 in the shot put. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the discus. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 60 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 800 meters. It found there was little significant difference in performance in time between women in 4, 5
F55 (classification)
16086502
put. It found there was little significant difference in performance in times between women in 1A and 1B in the 60 meters. It found there was little significant difference in performance in times between men in 1A and 1B in the 60 meters. It found there was little significant difference in performance in times between women in 1A and 1B in the slalom. It found there was little significant difference in performance in distance between women in 1A, 1B and 1C in the discus. It found there was little significant difference in performance in distance between women in 1A, 1B
T52 (classification)
16075241
little significant difference in performance times between men in 2 (SP4) and 3 (SP4, SP5) in the 50m breaststroke. It found there was little significant difference in performance times between women in 2 (SP4) and 3 (SP4, SP5) in the 50m freestyle. It found there was little significant difference in performance times between men in 2 (SP4) and 3 (SP4, SP5) in the 50m freestyle. It found there was little significant difference in performance times between men in 2 (SP4) and 3 (SP4, SP5) in the 50m backstroke. It found there was little significant difference in performance times between women
S3 (classification)
1296880
more explicitly human, although Huangdi, the Yellow Emperor, is often portrayed as part dragon during life. Some historicized versions of semi-historical and undeniably mythologized accounts of ancient times those who have, upon evidence such as tradition and archeoastronomy, apply actual BCE dates to the mythological chronology. Traditional Chinese accounts of the early emperors chronologically locate the Yellow Emperor as having lived in the Northern Chinese plain around 2698 to 2599 BCE (Wu 1982, 61), about seventeen generations after the time of Shennong (Wu 1982, 56 and 100 n. 25). A major difference between the possible historicity of material embedded in
Chinese mythology
8454113
is available concerning the importance of differences, the most important difference is selected first to further improve the average performance of MEA over other brute-force search strategies. However, even without the ordering of differences according to importance, MEA improves over other search heuristics (again in the average case) by focusing the problem solving on the actual differences between the current state and that of the goal. The MEA technique as a problem-solving strategy was first introduced in 1961 by Allen Newell and Herbert A. Simon in their computer problem-solving program General Problem Solver (GPS). In that implementation, the correspondence between
Means-ends analysis
12614961
Budgeted cost of work performed Budgeted Cost for Work Performed (BCWP) also called Earned Value (EV), is the budgeted cost of work that has actually been performed in carrying out a scheduled task during a specific time period. The BCWP is the sum of the budgets for completed work packages and completed portions of open work packages, plus the applicable portion of the budgets for level of effort and apportioned effort. (The items identified in the Work breakdown structure plus overhead costs, plus costs related in proportion to the planning and performance.) BCWP is a term in Earned value management
Budgeted cost of work performed
7774692
Prime gap A prime gap is the difference between two successive prime numbers. The "n"-th prime gap, denoted "g" or "g"("p") is the difference between the ("n" + 1)-th and the "n"-th prime numbers, i.e. We have "g" = 1, "g" = "g" = 2, and "g" = 4. The sequence ("g") of prime gaps has been extensively studied; however, many questions and conjectures remain unanswered. The first 60 prime gaps are: By the definition of "g" every prime can be written as The first, smallest, and only odd prime gap is the gap of size 1 between 2, the
Prime gap
6653674
Real prices and ideal prices The distinction between real prices and ideal prices is a distinction between "actual prices paid" for products, services, assets and labour (the net amount of money that actually changes hands), and "computed" prices which are not actually charged or paid in market trade, although they may facilitate trade. The difference is between actual prices "paid", and information about "possible", "potential" or "likely" prices, or "average" price levels. This distinction should not be confused with the difference between "nominal prices" (current-value) and "real prices" (adjusted for price inflation, and/or tax and/or ancillary charges). It is more
Real prices and ideal prices
19637793
in the 60 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 800 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 1,500 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the slalom. It found there was little significant difference in performance in distance between men in 4, 5 and 6in the discus. It found there was little significant difference in performance in distance
F56 (classification)
19637765
in the 60 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 800 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 1,500 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the slalom. It found there was little significant difference in performance in distance between men in 4, 5 and 6 in the discus. It found there was little significant difference in performance in
F57 (classification)
16075209
significant difference in performance times between women in 2 (SP4) and 3 (SP4, SP5) in the 50m freestyle. It found there was little significant difference in performance times between men in 2 (SP4) and 3 (SP4, SP5) in the 50m freestyle. It found there was little significant difference in performance times between men in 2 (SP4) and 3 (SP4, SP5) in the 50m backstroke. It found there was little significant difference in performance times between women in 4 (SP5, SP6), 5 (SP6, SP7) and 6 (SP7) in the 100m breaststroke. It found there was little significant difference in performance times
S4 (classification)
16075204
1C in the 25m freestyle. It found there was little significant difference in performance times between women in 2 and 3 in the 50m breaststroke. It found there was little significant difference in performance times between men in 2 (SP4) and 3 (SP4, SP5) in the 50m breaststroke. It found there was little significant difference in performance times between women in 2 (SP4) and 3 (SP4, SP5) in the 50m freestyle. It found there was little significant difference in performance times between men in 2 and 3 in the 50m freestyle. It found there was little significant difference in performance
S4 (classification)
16075235
and their balance. A study of was done comparing the performance of athletics competitors at the 1984 Summer Paralympics. It found there was little significant difference in performance times between women in 1A (SP1, SP2), 1B (SP3), and 1C (SP3, SP4) in the 25m breaststroke. It found there was little significant difference in performance times between women in 1A, and 1C in the 25m backstroke. It found there was little significant difference in performance times between women in 1A, 1B, and 1C in the 25m freestyle. It found there was little significant difference in performance times between men in 1A,
S3 (classification)
19650327
their hands. A study of was done comparing the performance of athletics competitors at the 1984 Summer Paralympics. It found there was little significant difference in performance times between women in 2 (SP4) and 3 (SP4, SP5) in the 50m breaststroke. It found there was little significant difference in performance times between men in 2 (SP4) and 3 (SP4, SP5) in the 50m breaststroke. It found there was little significant difference in performance times between women in 2 (SP4) and 3 (SP4, SP5) in the 50m freestyle. It found there was little significant difference in performance times between men in
F5 (classification)
16075199
competitor were allowed. A study of was done comparing the performance of athletics competitors at the 1984 Summer Paralympics. It found there was little significant difference in performance times between women in 1A (SP1, SP2), 1B (SP3), and 1C (SP3, SP4) in the 25m breaststroke. It found there was little significant difference in performance times between women in 1A, 1B, and 1C in the 25m backstroke. It found there was little significant difference in performance times between women in 1A, 1B, and 1C in the 25m freestyle. It found there was little significant difference in performance times between men in
S4 (classification)
9931795
reference value, the absolute difference can be considered in place of the actual change. The absolute difference between two values is not always a good way to compare the numbers. For instance, the absolute difference of 1 between 6 and 5 is more significant than the same absolute difference between 100,000,001 and 100,000,000. We can adjust the comparison to take into account the "size" of the quantities involved, by defining, for positive values of "x": The relative change is not defined if the reference value ("x") is zero. For values greater than the reference value, the relative change should be
Relative change and difference
19650387
in performance in time between men in 4, 5 and 6 in the 800 meters. It found there was little significant difference in performance in time between men in 4, 5 and 6 in the 1,500 meters. It found there was little significant difference in performance in time between men in 4, 5 and 6 in the slalom. It found there was little significant difference in performance in distance between women in 5 and 6 in the discus. It found there was little significant difference in performance in time between women in 5 and 6 in the 60 meters. It
F7 (classification)
19650319
performance in distance between women in 4, 5 and 6 in the discus. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the javelin. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the shot put. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the discus. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the 60 meters. It
F5 (classification)
19650289
in performance times between women in 1A (SP1, SP2), 1B (SP3), and 1C (SP3, SP4) in the 25m breaststroke. It found there was little significant difference in performance times between women in 1A, and 1C in the 25m backstroke. It found there was little significant difference in performance times between women in 1A, 1B, and 1C in the 25m freestyle. It found there was little significant difference in performance times between men in 1A, 1B, and 1C in the 25m backstroke. It found there was little significant difference in performance times between men in 1A, 1B, and 1C in the
F4 (classification)
19637821
performance in time between women in 3, 4 and 5 in the 60 meters. It found there was little significant difference in performance in distance between men in 3 and 4 in the javelin. It found there was little significant difference in performance in distance between men in 3 and 4 in the shot put. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the discus. It found there was little significant difference in performance in distance between women in 4, 5 and 6 in the javelin. It found there
F55 (classification)
19637819
in performance in distance between men in 2 (SP4) and 3 in the javelin. It found there was little significant difference in performance in distance between men in 2 (SP4) and 3 in the shot put. It found there was little significant difference in performance in time between men in 2 (SP4) and 3 in the 100 meters. It found there was little significant difference in performance in time between men in 2 (SP4) and 3 in the 200 meters. It found there was little significant difference in performance in time between men in 2 (SP4) and 3 in the
F55 (classification)
19650282
in performance in distance between men in 2 (SP4) and 3 (SP4, SP5) in the javelin. It found there was little significant difference in performance in distance between men in 2 (SP4) and 3 (SP4, SP5) in the shot put. It found there was little significant difference in performance in time between men in 2 (SP4) and 3 (SP4, SP5) in the 100 meters. It found there was little significant difference in performance in time between men in 2 (SP4) and 3 (SP4, SP5) in the 200 meters. It found there was little significant difference in performance in time between
F4 (classification)
16086557
performance in times between women in 1A (SP1, SP2) and 1B (SP3) in the 60 meters. It found there was little significant difference in performance in times between men in 1A (SP1, SP2) and 1B (SP3) in the 60 meters. It found there was little significant difference in performance in times between women in 1A (SP1, SP2) and 1B (SP3) in the slalom. It found there was little significant difference in performance in distance between women in 1B (SP3) and 1C (SP3, SP4) in the shot put. It found there was little significant difference in performance in time between women
T53 (classification)
9757563
For a dataset with "n" measurements, the set of all possible one- or two-element subsets of it has "n"("n" + 1)/2 elements. For each such subset, the mean is computed; finally, the median of these "n"("n" + 1)/2 averages is defined to be the Hodges–Lehmann estimator of location. The Hodges–Lehmann statistic also estimates the difference between two populations. For two sets of data with "m" and "n" observations, the set of two-element sets made of them is their Cartesian product, which contains "m" × "n" pairs of points (one from each set); each such pair defines one difference of values.
Hodges–Lehmann estimator
19650386
5 and 6 in the 1,500 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the slalom. It found there was little significant difference in performance in distance between men in 4, 5 and 6 in the discus. It found there was little significant difference in performance in distance between men in 4, 5 and 6 in the shot put. It found there was little significant difference in performance in time between men in 4, 5 and 6 in the 100 meters. It found there was little significant difference
F7 (classification)
19650318
3, 4,5 and 6 in the discus. It found there was little significant difference in performance in time between men in 3, 4,5 and 6 in the 200 meters. It found there was little significant difference in performance in time between women in 3, 4 and 5 in the 60 meters. It found there was little significant difference in performance in distance between men in 3 and 4 in the javelin. It found there was little significant difference in performance in distance between men in 3 and 4 in the shot put. It found there was little significant difference in
F5 (classification)
19637823
and 6 in the 1,500 meters. It found there was little significant difference in performance in time between women in 4, 5 and 6 in the slalom. It found there was little significant difference in performance in distance between men in 4, 5 and 6 in the discus. It found there was little significant difference in performance in distance between men in 4, 5 and 6 in the shot put. It found there was little significant difference in performance in time between men in 4, 5 and 6 in the 100 meters. It found there was little significant difference in
F55 (classification)
19637818
(SP4) and 3 in the 60 meters. It found there was little significant difference in performance in time between women in 2 (SP4) and 3 in the 200 meters. It found there was little significant difference in performance in time between women in 2 (SP4) and 3 in the 400 meters. It found there was little significant difference in performance in time between women in 2 (SP4) and 3 in the slalom. It found there was little significant difference in performance in distance between men in 2 (SP4) and 3 in the discus. It found there was little significant difference
F55 (classification)
321216
model and for a finite metal with the free electron approximation. Conjugated polyene systems can be modeled using particle in a box. The conjugated system of electrons can be modeled as a one dimensional box with length equal to the total bond distance from one terminus of the polyene to the other. In this case each pair of electrons in each π bond corresponds to one energy level. The energy difference between two energy levels, n and n is: formula_84 The difference between the ground state energy, n, and the first excited state, n+1, corresponds to the energy required to
Particle in a box
19637820
400 meters. It found there was little significant difference in performance in distance between women in 2 (SP4), 3 and 4 in the discus. It found there was little significant difference in performance in time between men in 2 (SP4), 3 and 4 in the 100 meters. It found there was little significant difference in performance in distance between women in 2 (SP4), 3, 4,5 and 6 in the discus. It found there was little significant difference in performance in time between men in 3, 4,5 and 6 in the 200 meters. It found there was little significant difference in
F55 (classification)
16086556
there was little significant difference in performance in distance between men in 1A (SP1, SP2) and 1B (SP3) in the club throw. It found there was little significant difference in performance in distance between men in 1A (SP1, SP2) and 1B (SP3) in the discus. It found there was little significant difference in performance in distance between men in 1A (SP1, SP2) and 1B (SP3) in the javelin. It found there was little significant difference in performance in distance between men in 1A (SP1, SP2) and 1B (SP3) in the shot put. It found there was little significant difference in
T53 (classification)