Methodology Of The Parametric Estimating Appropriate

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Methodology Of The Parametric Estimating Appropriate

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Methodology Of The Parametric Estimating Appropriate

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Is the methodology of parametric estimating appropriate to projects in the non-engineering domain, such as welfare projects? Is so then how is that the case? If not then why is that the case?

Answer:

Introduction:
In this report the article that will be reviewed is Aspect of Complexity by Terry Cooke-Davies. In the following paper the main topic of the discussion will be parametric estimating. COMPLEX PROJECT MANAGEMENT In the following paper discussion will be made on parametric estimating that can it be used in the non-engineering domain like the welfare projects. The justification will also be discussed in the following paper.
Parametric Estimation in Non-Engineering:
The parametric estimation is the process to estimate the time and the cost for the project more accurately than the other projects. The parametric estimation uses the relationship of the variables to calculate the accurate duration and the cost for the project (Martin & Pham, 2015). The parametric estimate is determined by the unit of time and by unit of cost. In the article or Terry Cooke it says many aspects of the parametric estimating. There are many different approach that the parametric model estimation takes:

Identification of the parametric model cot and then return the value to the ROI (Return on Investment).
Limitations and the assumptions are made.
Past data is gathered for the relevant project which will include the design data, technical data, cost and schedule (Kurkela & Zhu, 2015).
The data that are collected then normalized for quantities, economics, production rate, and for unit measurement.
Then the independent variables related to the for the cost drivers.
Depending in these independent variable a hypothesis is formulated.
To determine the significance, hypothesis is tested significantly (Berges et al., 2017).
For the further usage cost estimation is documented.

As per the discussion in the article is shows that the parametric estimating is only used in the project those are using technical work. Many kind of technological maturity models are used in the parametric estimation. Though it is also possible for the non-engineering project to use the parametric estimation (Heess et al., 2015).

Justification:
In the above paragraph it has been said that the parametric estimation can be used in the non-engineering projects. The project can be use the parametric estimating if they are having the requirement of the method. Every project has their assumed time and cost estimation and based on that the estimation methods are used (Cespedes & Sun, 2014). Is it an engineering project or non-engineering project it must assess the cost and the duration of the project. A project must have the minimum requirement like the cost and the project duration. If the project is having these data hen the parametric estimation will collect these data and then normalize the data as per the project requirements (Guo et al., 2014). A hypothesis is made for the project to analyse the data that are collected earlier. The hypothesis shows the progress of the project which is associated with duration and the time of the project. The non-engineering project like the welfare projects also have their fixed budget according to the project development time. The non-engineering projects are different from the projects of the engineering projects. The most of the parts are consists of the technical work in the engineering project where as in the non-engineering project there are less number of technical work (Brockwell & Schlemm, 2013). There are several common aspects are also presented on both of the engineering and non-engineering projects. The main aspect of the all is the budget and duration of the project which is present in the both kind of project and the whole project is dependent on these aspects. The material suppliers and he manufacturing process providers are also same in the both projects as these the things are required for every kind of project irrespective of the project type. In the paper of Terry Cooke it says that the main problem of the project are in the part of the technologies which are mature but do not have the capability. In the non-engineering project parametric model is also used for determining the requirements. In the non-engineering project limitations and the assumptions are made. Every project that are of non-engineering has past data which can be sued for developing the future projects. As per the requirement of the project these data are normalized (Matzke et al., 2013). And the cost drivers are also assessed in these project. Hypothesis also made to see the success of the project and the project significance. These are the factors for what parametric estimating can be used in the projects of the non-engineering like the welfare project or other projects.
Conclusion:
In the above report the main discussion is made on the parametric estimation. In the above report it has been said that the parametric estimating can be used in the non-engineering projects. The factors on which the parametric estimation works are more or less same in the both projects.

References:
Babadi, B., & Brown, E. N. (2014). A review of multitaper spectral analysis. IEEE Trans. Biomed. Engineering, 61(5), 1555-1564.
Berges, J., Reygers, K., Tanji, N., & Venugopalan, R. (2017). Parametric estimate of the relative photon yields from the glasma and the quark-gluon plasma in heavy-ion collisions. Physical Review C, 95(5), 054904.
Brockwell, P. J., & Schlemm, E. (2013). Parametric estimation of the driving Lévy process of multivariate CARMA processes from discrete observations. Journal of Multivariate Analysis, 115, 217-251.
Cespedes, M., & Sun, J. (2014). Adaptive control of grid-connected inverters based on online grid impedance measurements. IEEE Transactions on sustainable energy, 5(2), 516-523.
Guo, X., Liu, H., Mao, X., Jin, J., Chen, D., & Cheng, S. (2014). Willingness to pay for renewable electricity: A contingent valuation study in Beijing, China. Energy Policy, 68, 340-347.
Heess, N., Wayne, G., Silver, D., Lillicrap, T., Erez, T., & Tassa, Y. (2015). Learning continuous control policies by stochastic value gradients. In Advances in Neural Information Processing Systems (pp. 2944-2952).
Kurkela, A., & Zhu, Y. (2015). Isotropization and hydrodynamization in weakly coupled heavy-ion collisions. Physical review letters, 115(18), 182301.
Martin, W., & Pham, C. S. (2015). Estimating the gravity model when zero trade flows are frequent and economically determined. The World Bank.
Matzke, D., Dolan, C. V., Logan, G. D., Brown, S. D., & Wagenmakers, E. J. (2013). Bayesian parametric estimation of stop-signal reaction time distributions. Journal of Experimental Psychology: General, 142(4), 1047.

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