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Normative issues associated with income inequality are discussed. A review of the debate over Paglin’s basic revision of the Gini coefficient is presented. The methodology for computing some alternative measures of income inequality is described.

This chapter covers the design, analysis, and interpretation of validity and reliability studies, particularly for exposure measures used in epidemiologic studies. It covers both intramethod (e.g., test-retest) reliability studies and intermethod reliability studies (e.g., in which a measurement method to be used in an epidemiological study is compared to a more accurate but not perfect method). Measures of reliability are primarily important for what they reveal about the validity of a measure, and this concept is emphasized for both design and interpretation of reliability studies. The choice of an analysis technique depends on whether the exposure is measured as a continuous variable or a categorical variable and whether the study is a validity or intermethod study vs. an intramethod study. For intramethod studies, versions of the intraclass correlation coefficient are used for continuous exposure variables and versions of kappa are used for categorical variables.

This chapter analyzes why a business or a project fails to meet its debt-service commitments. It is devoted to a full-scale credit risk analysis of a lending decision and pricing of a particular risk category of a borrower, using real-life examples. The approach is kept simple and practical, so that the system proposed can be easily implemented by lending organisations.

This chapter discusses the amplitude of population change in a variety of small rodent species, focusing on the latitudinal variations in population variability and population density. The coefficient of variation is used to measure population variability. The chapter begins by identifying the data needed to calculate the coefficient of variation. It then addresses whether population fluctuations are stronger at high latitudes and whether small rodent maximum densities are higher in more productive habitats or lower in predator-rich habitats.

This chapter reviews the most widely used metrics to analyze mutual fund performance. It covers tools, risk metrics, and rating criteria popular with both academics and practitioners. Measurement of relative fund performance is tested with a set of dimensionless ratios including the coefficient of variation, Sharpe ratio, and Treynor ratio. Interpreting the precise amount of relative under- or over-performance is difficult with dimensionless ratios. In response to this drawback of using such measures, several researchers developed mutual fund performance metrics that quantify risk-adjusted performance to a greater degree. For example, the M² measure, Jensen’s alpha, and the Carhart model are useful in quantifying risk-adjusted performance in percentage terms. The chapter presents recent extensions or enhancements to the Carhart model and also discusses the quantitative and qualitative risk metrics available from Morningstar.

Scale is now a central topic of research and theory in rangeland ecology, and non-equilibrium ideas have rapidly gained footing in the US and globally. But the problem of scale remains a daunting obstacle to effective rangeland management. Current scientific research indicates that areas with a high coefficient of variation of rainfall are dominated by non-equilibrium ecological dynamics. Highly variable precipitation still defies the temporal demands of capital accumulation, and climate change is projected to increase variability still further. The history of range science could have been different: scientists might have worked more closely with livestock producers to vary stocking rates, and rangelands might have been managed at larger scales, as in the case of the Mizpah-Pumpkin Creek Grazing District in southeastern Montana in the late 1920s. Community-based conservation groups have flourished throughout the West in recent decades, committed to collaborative approaches that permit greater flexibility and adaptive management at landscape scales. Science cannot be abstracted from its social contexts, and knowledge cannot be separated from the social processes that produce and condition it.