Spelling suggestions: "subject:"degression equations"" "subject:"aregression equations""
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Retail Site Selection Using Multiple Regression AnalysisTaylor, Ronald D. (Ronald Dean) 12 1900 (has links)
Samples of stores were drawn from two chains, Pizza Hut and Zale Corporation. Two different samples were taken from Pizza Hut. Site specific material and sales data were furnished by the companies and demographic material relative to each site was gathered. Analysis of variance tests for linearity were run on the three regression equations developed from the data and each of the three regressions equations were found to have a statistically significant linear relationship. Statistically significant differences were found among similar variables used in the prediction of sales by using Fisher's Z' Transformations on the correlation coefficients. Eight of the eighteen variables used in the Pizza Hut study were found to be statistically different between the two regions used in the study. Additionally, analysis of variance tests were used to show that traffic pattern variables were not better predictors than demographic variables.
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NRCS Curve Number Calibration Using USGS Regression EquationsMecham, Charlotte M. 18 April 2008 (has links) (PDF)
The Curve Number (CN) method of estimating the direct runoff response to rainfall events was originally developed in the 1950's primarily for agricultural purposes in the mid-western United States. The accuracy of the CN method is greatly affected by variation of the soil type and land use of the region. Curve Numbers developed for a given region are not appropriate for application in other regions. In order to produce reliable, consistent results, Curve Numbers must be calibrated for the area in which the CN method is to be applied. Calibration is ideally accomplished by direct measurement using several rain and stream gauges within a watershed. Gauged data, however, is not always available or easily obtained. A more feasible method of calibration is therefore necessary for broad application of the CN method. The purpose of this study is to develop a method of CN calibration that can be easily applied to regions where no gauged data is available using the United States Geological Survey (USGS) regression equations. In this study, the peak flow values estimated using the regression equations were used in conjunction with a dimensionless hydrograph to compute runoff volume. The National Oceanic and Atmospheric Administration (NOAA) rainfall grids were used to estimate precipitation. Given the rainfall and runoff, a Curve Number can then calibrated through back-calculation. The method of CN calibration using the USGS regression equations was applied to nearly 60 watersheds in the state of Utah for this research. The calibration results obtained using the regression equations were compared to other CN calibrations developed using gauged data. Calibrations performed through the use of the regression equations were quite consistent with calibrations obtained using measured data. To ensure the validity of the application of this method in other regions, more comparisons to results obtained using measured data should be further pursued.
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Pagrindinių kiaulių veislių ir jų mišrūnų skerdenos kokybės savybių tyrimai / Investigation of carcass quality characteristics of the main pig breeds and their crossbredsMikelėnas, Aurelijus 25 April 2005 (has links)
Novelty of the research. The effect of genetic and environmental factors on the lean meat quantity in the carcass and the growth rate has been determined by the method of ANOVA for the first time in the country, LW and other breed improvers were highlighted. Statistically reliable regression equations of ham muscle output prediction were drawn. Relations of four main parts of the carcass and their interaction with the carcass quality indexes was defined. Influence of bone fibre myocytes towards the lean meat in the carcass, and the relation between the pH and carcass quality, were analysed.
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Impacts of Stationarity Assumption in Floodplain Management: Case StudiesPalmer, Laura Michelle 08 August 2017 (has links)
No description available.
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