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A design of experiment of DSLR image clarity: An experimental economic analysis

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  • Chen, Lishu

Abstract

This research is focused on randomized designs, two-stage experiments that first randomize treatment of a group, then investigate on the significant factors with economic perspective. It is attempted to map the potential outcomes framework with partial interference to a regression model with clustered errors, calculate standard errors of randomized saturation designs. The objective of this study is to assess the clarity of a photographic image produced by a DSLR camera by varying relevant factors such as image distance, shutter speed, aperture etc with on impact financial support. The criterion for assigning the ranking was the ability of clearly seeing the object in the photographs and the sharpness of the object. Design of experiments (DOE)-based approach allows for an efficient estimation of the main effects and the interactions with minimal number of experiments. This study investigates the factors that are mostly responsible for DSLR image clarity. All the six factors are set in two levels to create a full-factorial 2k design. A residual analysis has been done to test for defects such as non-normality, non-independent and non-constant variance. Based upon this evidence, we assert that (DOE)-based approach valuation information has the potential to negatively impact financial support for the exact resources the information is designed to promote and holds considerable potential for experimental economics, deserves greater attention as a methodological tool, and promises important insights on strategic decision making.

Suggested Citation

  • Chen, Lishu, 2018. "A design of experiment of DSLR image clarity: An experimental economic analysis," MPRA Paper 90949, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:90949
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    File URL: https://mpra.ub.uni-muenchen.de/90949/1/MPRA_paper_90949.pdf
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    References listed on IDEAS

    as
    1. Zhang, Wei & (Ato) Xu, Wangtu, 2017. "Simulation-based robust optimization for the schedule of single-direction bus transit route: The design of experiment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 203-230.
    2. Goff, Sandra H. & Waring, Timothy M. & Noblet, Caroline L., 2017. "Does Pricing Nature Reduce Monetary Support for Conservation?: Evidence From Donation Behavior in an Online Experiment," Ecological Economics, Elsevier, vol. 141(C), pages 119-126.
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    More about this item

    Keywords

    Design of Experiment (DOE); Full Factorial Design; ANOVA; Economic and Statistical Analysis; Experimental Economics;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

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