IJRESS Volume 1‚ Issue 1(October‚ 2011) (ISSN 2249-7382) A STUDY OF TRAINING IN INSURANCE AND THEIR IMPACT ON EMPLOYEES PRODUCTIVITY Dr. Shefali Verma* Rita Goyal** ABSTRACT The training and development function plays a further enhanced role and holds more importance‚ as it deals with knowledge of workers .Employees are entrusted different roles and responsibilities in the LIC. Training enables them to carry out these roles and responsibilities efficiently and also learn new things‚ which will
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------------------------------------------------- “India’s economy would reap a better demographic dividend and would grow faster in the next decade” As compared to China‚ do you believe India will have a bigger advantage? Examine how your company is gearing up to benefit from the economic Boom in both the countries? Definitely‚ I believe that India will have a bigger advantage when compared to china due to a better demographic dividend. China & India are the two largest populations in the world‚ each has over a billion
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MC-B TOPIC; LINEAR PROGRAMMING DATE; 5 JUNE‚ 14 UNIVERSITY OF CENTRAL PUNJAB INTRODUCTION TO LINEAR PROGRAMMING Linear programming (LP; also called linear optimization) is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships. Linear programming is a special case of mathematical programming
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eurojournals.com Dividend Policy: A Review of Theories and Empirical Evidence Husam-Aldin Nizar Al-Malkawi Corresponding Author‚ Faculty of Business‚ ALHOSN University P.O. Box 38772 - Abu Dhabi‚ UAE E-mail: h.almalkawi@alhosnu.ae Michael Rafferty Senior Research Analyst‚ WRC‚ University of Sydney‚ Australia E-mail: m.rafferty@econ.usyd.edu.au Rekha Pillai Faculty of Business‚ ALHOSN University‚ Abu Dhabi‚ UAE E-mail: r.pillai@alhosnu.ae Abstract The literature on dividend policy has produced a large
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Linear Programming History of linear programming goes back as far as 1940s. Main motivation for the need of linear programming goes back to the war time when they needed ways to solve many complex planning problems. The simplex method which is used to solve linear programming was developed by George B. Dantzig‚ in 1947. Dantzig‚ was one in who did a lot of work on linear programming‚ he was reconzied by several honours. Dantzig’s discovery was through his personal contribution‚ during WWII when Dantzig
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Dividend irrelevance theoryRelevance or irrelevance of retention for dividend policy irrelevance Carlo Alberto Magni Department of Economics‚ University of Modena and Reggio Emilia viale Berengario 51‚ 41100 Modena‚ Italy Email: magni@unimo.it Abstract. In an interesting recent paper‚ DeAngelo and DeAngelo (2006) highlight that Miller and Modigliani’s (1961) proof of dividend irrelevance is based on the assumption that the amount of dividends distributed to shareholders is equal or greater than
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Duality in Linear Programming 4 In the preceding chapter on sensitivity analysis‚ we saw that the shadow-price interpretation of the optimal simplex multipliers is a very useful concept. First‚ these shadow prices give us directly the marginal worth of an additional unit of any of the resources. Second‚ when an activity is ‘‘priced out’’ using these shadow prices‚ the opportunity cost of allocating resources to that activity relative to other activities is determined. Duality in linear programming
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2014/9/16 Linear Equations Ad Options Ads by Vidx Linear Equations A linear equation is an equation for a straight line These are all linear equations: y = 2x+1 5x = 6+3y y/2 = 3 x Let us look more closely at one example: Example: y = 2x+1 is a linear equation: The graph of y = 2x+1 is a straight line When x increases‚ y increases twice as fast‚ hence 2x When x is 0‚ y is already 1. Hence +1 is also needed So: y = 2x + 1 Here are some example values: http://www.mathsisfun.com/algebra/linear-equations
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Plots Linear regression is a crucial tool in identifying and defining key elements influencing data. Essentially‚ the researcher is using past data to predict future direction. Regression allows you to dissect and further investigate how certain variables affect your potential output. Once data has been received this information can be used to help predict future results. Regression is a form of forecasting that determines the value of an element on a particular situation. Linear regression
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Introduction Linear optimization is a mathematical method for determining a way to achieve the best outcome such as maximum profit or lowest cost in a given mathematical model for some list of requirements represented as linear relationships. Linear programming is a specific case of mathematical programming The Primary Purpose of the present investigation is to develop an interactive spreadsheet tool to aid in determining a maximum return function in 401K plan. In this paper‚ we discuss how the
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