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1

Guth, Scott. Elementary statistics: Managing variability and error. Mt. San Antonio College, 2006.

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2

Singh, Nityanand. Climatic and hydroclimatic features of wet and dry spells and their extremes across India. Indian Institute of Tropical Meteorology, 2009.

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3

Weisberg, Herbert F. Central tendency and variability. Sage Publications, 1992.

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4

Barnston, A. G. Atlas of frequency distribution, auto-correlation and cross-correlation of daily temperature and precipitation at stations in the U.S., 1948-1991 (in English units). U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, 1993.

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5

Barnston, A. G. Atlas of frequency distribution, auto-correlation and cross-correlation of daily temperature and precipitation at stations in the U.S., 1948-1991 (in metric units). U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, 1993.

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6

Zhang, J. C. Yield and variability optimization of integrated circuits. Kluwer Academic Publishers, 1995.

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7

International Conference on Soft Methods in Probability and Statistics (4th 2008 Toulouse, France). Soft methods for handling variability and imprecision. Springer Verlag, 2008.

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8

Robeson, Scott M. Spatial interpolation, network bias, and terrestrial air temperature variability. C.W. Thornthwaite Associates, Laboratory of Climatology, 1993.

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9

D, Schertzer, and Lovejoy S. 1956-, eds. Non-linear variability in geophysics: Scaling and fractals. Kluwer Academic Publishers, 1991.

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10

D, Miller Christopher, United States. Minerals Management Service. Pacific OCS Region., and Greenhorne & O'Mara., eds. An Initial statistical characterization of the variability of coastal winds and currents. U.S. Dept. of the Interior, Minerals Management Service, Pacific OCS Region, 1991.

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11

D, Miller Christopher, United States. Minerals Management Service. Pacific OCS Region., and Greenhorne & O'Mara., eds. An Initial statistical characterization of the variability of coastal winds and currents. U.S. Dept. of the Interior, Minerals Management Service, Pacific OCS Region, 1991.

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12

Gao, Xiaohong. Sampling variability and generalizability of Word Keys listening and writing scores. American College Testing Program, 1996.

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13

W, Stutte G., and United States. National Aeronautics and Space Administration., eds. Statistical analysis of environmental variability within the CELSS Breadboard Project's Biomass Production Chamber. National Aeronautics and Space Administration, 1993.

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14

W, Stutte G., and United States. National Aeronautics and Space Administration., eds. Statistical analysis of environmental variability within the CELSS Breadboard Project's Biomass Production Chamber. National Aeronautics and Space Administration, 1993.

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15

Fielder, Lonnie L. Measurement of price, yield, and revenue variability for Louisiana crops. Dept. of Agricultural Economics and Agribusiness, Louisiana Agricultural Experiment Station, Louisiana State University Agricultural Center, 1985.

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16

Campbell, Jeffrey W. Evaluation of GEOSTAT data and application to variability of the Northeast Pacific Ocean. Woods Hole Oceanographic Institution, 1988.

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17

D, Miller Christopher, United States. Minerals Management Service. Pacific OCS Region., and Greenhorne & O'Mara., eds. An Initial statistical characterization of the variability of coastal winds and currents: Executive summary. U.S. Dept. of the Interior, Minerals Management Service, Pacific OCS Region, 1991.

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18

Hansen, S. Spatial variability of soil physical properties: Theoretical and experimental analyses : II. Soil water variables--data acquisition, processing and basic statistics. Dept. of Soil and Water and Plant Nutrition, Royal Veterinary and Agricultural University, 1988.

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19

Forest, Paul. Variabilité des caractéristiques socio-économiques des ménages selon le type d'agglomération au Québec en 1996. Société d'habitation du Québec, Direction de la planification, de l'évaluation et de la recherche, 2001.

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20

Atlantic Oceanographic and Meteorological Laboratories, ed. The variability of surface-air temperature and precipitation at Miami International Airport including relationships with tropical weather system activity and El Niño: 1941-1990. Atlantic Oceanographic and Meteorological Laboratory, U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, 1994.

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21

Różdżyński, Kazimierz. Micro-variability of characteristics of thermo- and hygrometric circuits in automatic meteorological stations of the State Hydrological Meteorological Service (PSHM). Institute of Meteorology and Water Management, National Research Institute, 2013.

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22

Goetz, Carole L. Adequacy of NASQAN data to describe areal and temporal variability of water quality of the San Juan River drainage basin upstream from Shiprock, New Mexico. Dept. of the Interior, U.S. Geological Survey, 1987.

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23

1949-, Storch H. v., Navarra A. 1956-, and Commission of the European Communities., eds. Analysis of climate variability: Applications of statistical techniques : proceedings of an autumn school organized by the Commission of the European Community on Elba from October 30 to November 6, 1993. 2nd ed. Springer, 1999.

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24

Scruton, D. A. Spatial and temporal variability in the water chemistry of Atlantic salmon rivers in insular Newfoundland: An assessment of sensitivity to and effects from acidification and implications for resident fish. Fisheries Research Branch, Dept. of Fisheries and Oceans, 1986.

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25

L, Dryden I., Gill C. A, Mardia K. V, and Leeds Annual Statistical Research Workshop (16th : 1996 : Leeds, England), eds. Proceedings in image fusion and shape variability techniques: International conference, held in Leeds, UK, 3-5 July 1996, incorporating the 16th Leeds Annual Statistical Research (L.A.S.R.) Workshop ... Leeds University Press, 1996.

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26

Spinelli, Glenn Allan. A statistical analysis of ice-accummulation level and variability in the GISP2 ice core and a reexamination of the age of the termination of the Younger Dryas cooling episode. Pennsylvania State, Earth System Science Center, College of Earth & Mineral Sciences, 1996.

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27

author, Thompson Simon G., ed. Mendelian randomization: Methods for using genetic variants in causal estimation. CRC Press, Taylor & Francis Group, 2015.

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28

Nigro, Giampiero, ed. I prezzi delle cose / The Prices of Things. Firenze University Press, 2017. http://dx.doi.org/10.36253/978-88-6453-492-3.

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La dinamica dei prezzi è uno degli argomenti classici della storia economica. L’attenzione per questo tema fu particolarmente viva a partire dagli anni Trenta del Novecento, in tutti i paesi europei. I materiali raccolti e pubblicati a quell’epoca continuano a costituire una base documentaria importante per ogni ricerca sull’andamento economico delle economie pre-industriali. L’interesse per i prezzi si ridusse dagli anni Settanta agli anni Novanta. È ripreso, tuttavia, negli ultimi quindici-venti anni come conseguenza della rinnovata attenzione per il tema della crescita e per i cambiamenti d
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29

Wang, Cun. Zhong yuan di qu li shi han lao qi hou yan jiu he yu ce. Qi xiang chu ban she, 1992.

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30

Guth, Scott. Elementary Statistics Managing Variability and Error. Mt. San Antonio College, 2006.

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31

(Editor), H. von Storch, and A. Navarra (Editor), eds. Analysis of Climate Variability: Applications of Statistical Techniques. 2nd ed. Springer, 1999.

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32

Navarra, Antonio, and Hans v. Storch. Analysis of Climate Variability: Applications of Statistical Techniques. Springer London, Limited, 2013.

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33

Ball, Shane T. Statistical analysis of spring wheat variability in breeding experiments. 1991.

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34

Polyak, Ilya. Computational Statistics in Climatology. Oxford University Press, 1996. http://dx.doi.org/10.1093/oso/9780195099997.001.0001.

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Scientific descriptions of the climate have traditionally been based on the study of average meteorological values taken from different positions around the world. In recent years however it has become apparent that these averages should be considered with other statistics that ultimately characterize spatial and temporal variability. This book is designed to meet that need. It is based on a course in computational statistics taught by the author that arose from a variety of projects on the design and development of software for the study of climate change, using statistics and methods of rand
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35

(Editor), D. Schertzer, and S. Lovejoy (Editor), eds. Non-Linear Variability in Geophysics: Scaling and Fractals. Springer, 1990.

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36

Les gradients climatiques en Tunisie: Application à la température et à la pluie. Publications de la Faculté des lettres de la Manouba, 2000.

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37

Watanabe, Mari, Markad V. Kamath, Adrian R. M. Upton, and Carlos A. Morillo. Heart Rate Variability (Hrv) Signal Analysis. Taylor & Francis Group, 2012.

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38

Clarke, Andrew. Introduction. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199551668.003.0001.

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This introduces the subject, laying out the organisation of the book and emphasising the importance of both simple underlying physical mechanisms and evolutionary variability to thermal ecology. It distinguishes physical mechanism from statistical description, and the importance of evolutionary processes in comparisons across species.
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39

A Statistical Analysis of the Variability Experienced in DLA administrative and Production Lead Time. Storming Media, 1999.

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40

Howell, James Frederick. The influence of small scale variability on scaling relationships describing atmospheric turbulence. 1993.

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41

Food shortage, climatic variability, and epidemic disease in preindustrial Europe: The mortality peak in the early 1740s. Cornell University Press, 1985.

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42

Heart rate variability (HRV) signal analysis: Clinical applications. Taylor & Francis, 2013.

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43

Busuioc, Aristita, and Alexandru Dumitrescu. Empirical-Statistical Downscaling: Nonlinear Statistical Downscaling. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.770.

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This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Climate Science. Please check back later for the full article.The concept of statistical downscaling or empirical-statistical downscaling became a distinct and important scientific approach in climate science in recent decades, when the climate change issue and assessment of climate change impact on various social and natural systems have become international challenges. Global climate models are the best tools for estimating future climate conditions. Even if improvements can be made in state-of-the art
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44

Storch, H. V. Analysis of Climate Variability: Applications of Statistical Techniques : Proceedings of an Autumn School Organized by the Commission of the Europea. Springer, 1995.

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45

Mauranen, Anna. Second-Order Language Contact. Edited by Markku Filppula, Juhani Klemola, and Devyani Sharma. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199777716.013.010.

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This chapter discusses the nature of English as a lingua franca (ELF) as uniquely complex ‘second order language contact’, which arises from contact between ‘similects’ of speakers from given first language backgrounds. The data is drawn from speech in academic communities. ELF is best understood as operating on three levels: the macro-social, the micro-social, and the cognitive. English as a lingua franca is largely similar to English as a native language in comparable social circumstances, but it also manifests lexico-grammatical features that are clearly different: nonstandard grammatical a
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46

Congendo, Marco, and Fernando H. Lopes da Silva. Event-Related Potentials. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0039.

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Event-related potentials (ERPs) can be elicited by a variety of stimuli and events in diverse conditions. This chapter covers the methodology of analyzing and quantifying ERPs in general. Basic models (additive, phase modulation and resetting, potential asymmetry) that account for the generation of ERPs are discussed. The principles and requirements of ensemble time averaging are presented, along with several univariate and multivariate methods that have been proposed to improve the averaging procedure: wavelet decomposition and denoising, spatial, temporal and spatio-temporal filtering. We em
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47

Razo, Armando. Integration of Contextual Data. Edited by Lonna Rae Atkeson and R. Michael Alvarez. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.20.

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This chapter discusses a conceptual framework that clarifies the nature and importance of context in social scientific research. It first explains how context fits into survey analysis, then addresses major problems that hamper use and collection of contextual data: vague or incomplete conceptual definitions of “context” and lack of methodological guidance to collect and analyze contextual data. It suggests that systematic research and cumulative knowledge on contextual effects are constrained by two factors: the lack of standardized contextual variables across surveys and sporadic empirical i
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48

Cawvey, Matthew, Matthew Hayes, Damarys Canache, and Jeffery J. Mondak. Biological and Psychological Influences on Interpersonal and Political Trust. Edited by Eric M. Uslaner. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190274801.013.11.

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Levels of interpersonal and political trust undoubtedly ebb and flow in response to external stimuli. Despite the variability in one’s environment, there is good reason to believe that interpersonal and political trust also originate from individual characteristics. In this chapter, we focus on the impact of biology and personality on trust. Biological factors and personality traits constitute relatively stable individual differences that influence perceptions, evaluations, and orientations toward the social and political world. Research on trust has examined both of these influences, and we r
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49

Analysis of climate variability: Applications of statistical techniques : proceedings of an Autumn School organized by the Commission of the European Community on Elba from October 30 to November 6, 1993. Springer, 1995.

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50

Hirschman, Lynette, and Inderjeet Mani. Evaluation. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0022.

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The commercial success of natural language (NL) technology has raised the technical criticality of evaluation. Choices of evaluation methods depend on software life cycles, typically charting four stages — research, advance prototype, operational prototype, and product. At the prototype stage, embedded evaluation can prove helpful. Analysis components can be loose grouped viz., segmentation, tagging, extracting information, and document threading. Output technologies such as text summarization can be evaluated in terms of intrinsic and extrinsic measures, the former checking for quality and in
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