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{ "item_title" : "Statistical Methodologies", "item_author" : [" Jan Peter Hessling "], "item_description" : "Statistical practices have recently been questioned by numerous independent authors, to the extent that a significant fraction of accepted research findings can be questioned. This suggests that statistical methodologies may have gone too far into an engineering practice, with minimal concern for their foundation, interpretation, assumptions, and limitations, which may be jeopardized in the current context. Disguised by overwhelming data sets, advanced processing, and stunning presentations, the basic approach is often intractable to anyone but the analyst. The hierarchical nature of statistical inference, exemplified by Bayesian aggregation of prior and derived knowledge, may also be challenging. Conceptual simplified studies of the kind presented in this book could therefore provide valuable guidance when developing statistical methodologies, but also applying state of the art with greater confidence.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/78/923/997/1789239974_b.jpg", "price_data" : { "retail_price" : "155.00", "online_price" : "155.00", "our_price" : "155.00", "club_price" : "155.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Statistical Methodologies|Jan Peter Hessling

Statistical Methodologies

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Overview

Statistical practices have recently been questioned by numerous independent authors, to the extent that a significant fraction of accepted research findings can be questioned. This suggests that statistical methodologies may have gone too far into an engineering practice, with minimal concern for their foundation, interpretation, assumptions, and limitations, which may be jeopardized in the current context. Disguised by overwhelming data sets, advanced processing, and stunning presentations, the basic approach is often intractable to anyone but the analyst. The hierarchical nature of statistical inference, exemplified by Bayesian aggregation of prior and derived knowledge, may also be challenging. Conceptual simplified studies of the kind presented in this book could therefore provide valuable guidance when developing statistical methodologies, but also applying state of the art with greater confidence.

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Details

  • ISBN-13: 9781789239973
  • ISBN-10: 1789239974
  • Publisher: Intechopen
  • Publish Date: February 2020
  • Dimensions: 9.61 x 6.69 x 0.44 inches
  • Shipping Weight: 1.01 pounds
  • Page Count: 160

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