UML object diagram - Estimating scenario

"A cost estimate is the approximation of the cost of a program, project, or operation. The cost estimate is the product of the cost estimating process. The cost estimate has a single total value and may have identifiable component values. A problem with a cost overrun can be avoided with a credible, reliable, and accurate cost estimate. An estimator is the professional who prepares cost estimates. There are different types of estimators, whose title may be preceded by a modifier, such as building estimator, or electrical estimator, or chief estimator. Other professional titles may also prepare estimates or contribute to estimates, such as quantity surveyors, cost engineers, etc." [Cost estimate. Wikipedia]
The UML object diagram example "Estimating scenario" was created using the ConceptDraw PRO diagramming and vector drawing software extended with the Rapid UML solution from the Software Development area of ConceptDraw Solution Park.

This DFD sample was created on the base of figure illustrating the "Interactive Double Mass Analysis. User's Guide" from the website of the Office of Hydrologic Development of the National Weather Service (NWS) of the National Oceanic and Atmospheric Administration (NOAA).
"Double mass analysis is a technique commonly employed to determine corrections to hydrometeorological data to account for changes in data collection procedures or other local conditions. The changes may result from a variety of things including changes in instrumentation, changes in observation procedures, or changes in gage location or surrounding conditions. The purpose of this Interactive Double Mass Analysis (IDMA) tool is to provide an effective and efficient way for users to perform consistency checking using double mass analysis and to produce the correction factors that are used in subsequent processing by NWSRFS preprocessor tools to account for any discovered inconsistencies.
Computations of mean areal time series for use in calibration and ESP have traditionally been made using the appropriate preprocessing software (MAP, PXPP, MAT etc.). The preprocessors have traditionally taken point time series as input and have provided facilities for estimation of missing data, and for consistency checking and correction in addition to the mean areal computations. The IDMA tool has been designed to run in conjunction with the preprocessors in an iterative fashion. It performs the consistency checking function, leaving the estimation, correction and mean areal computations to the preprocessors. ...
As shown in Figure ... the preprocessor software generates a data file that contains accumulated data values for each station and the associated group base, as well as flags indicating whether the values were estimated or not. This data file along with the input card file used by the preprocessor are used by the IDMA tool. The IDMA tool then allows the user to perform consistency checks and to calculate correction factors. The correction factors are then returned so that the preprocessors can perform the corrections, re-estimate missing data and perform the mean areal computations. Note that there is an interdependence between the estimation of missing values in the preprocessors and the correction factors computed in the IDMA and so there needs to be iteration between the two processes until the user is satisfied that an appropriate balance has been reached."
[nws.noaa.gov/ oh/ hrl/ idma/ users_ guide/ html/ dma_ overview.php]
The example "Interaction between IDMA and preprocessor" was created using the ConceptDraw PRO diagramming and vector drawing software extended with the Data Flow Diagrams solution from the Software Development area of ConceptDraw Solution Park.

The vector stencils library "Histograms" contains 10 chart templates. Use it to design your histograms for visualizing frequency distribution data in ConceptDraw PRO diagramming and vector drawing software.
"In statistics, a histogram is a graphical representation of the distribution of data. It is an estimate of the probability distribution of a continuous variable...
A histogram is a representation of tabulated frequencies, shown as adjacent rectangles, erected over discrete intervals (bins), with an area equal to the frequency of the observations in the interval. The height of a rectangle is also equal to the frequency density of the interval, i.e., the frequency divided by the width of the interval. The total area of the histogram is equal to the number of data. A histogram may also be normalized displaying relative frequencies. It then shows the proportion of cases that fall into each of several categories, with the total area equaling 1. The categories are usually specified as consecutive, non-overlapping intervals of a variable. The categories (intervals) must be adjacent, and often are chosen to be of the same size. The rectangles of a histogram are drawn so that they touch each other to indicate that the original variable is continuous.
Histograms are used to plot the density of data, and often for density estimation: estimating the probability density function of the underlying variable. The total area of a histogram used for probability density is always normalized to 1." [Histogram. Wikipedia]
The chart templates example "Design elements - Histograms" is included in the Basic Histograms solution from the Graphs and Charts area of ConceptDraw Solution Park.