# Statistical Assumptions In Statistical Research

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All the statistical procedures have some underlying assumptions and more stringent than others. For some cases, the violation of assumptions will not change the substantive conclusions and for some different cases, violation of the assumptions will undermine meaningful research. Establishing the data, which meets the assumptions of procedures in using an expected component of all the quantitatively-based thesis, journal articles and dissertations. For all the volumes in the statistical associates ‘blue book’ series, is the one in which the assumptions of each statistical procedure are indicated. This volume provides an overview of most of the common data assumptions in, which a researcher encounters the statistical research. In this chapter…show more content…
If when these assumptions are violated then the results of analysis may be misleading. While testing multivariate analysis many assumptions can be made. In which the typical assumptions is Multicollinearity. A linear assumption between two explanatory variables is Collinearity. If two variables are perfectly collinear then there should be an exact linear relationship between them. Multicollinearity is a statistical phenomenon, and exists a perfect relationship between the predictor variables. For a perfect or exact relationship between the predictor variables, it will be difficult to come up with reliable estimates of individual coefficients. Multicollinearity inflates the variance of parameter estimates which leads to lack of statistical significance of individual predictor variables. For example, a multicollinear predictors may be height and weight of a person, years of education and income, assessed value and square footage of a…show more content…
They require the fundamental of the statistical methods, tools and techniques. These are strong for the managers who are applying to their works to organise, analyse and the data f or their business decisions. Managerial overview mainly focuses on the developing skills set and the correct applications of statistical tools and techniques, to make required decisions in the areas of business of both public and private. Results-Based Management (RBM) is a management strategy aimed for achieving the changes in a way organisations operate, by improving the performance in the terms of results. RBM provides management framework and tools for making strategic planning, performance, risk management, and evaluation. The primary purpose of RBM is to improve efficiency and effectiveness through organisational learning and to fulfil accountability obligations by performing reporting. These include finance, account keeping, marketing, human resource, production management, gathering data, examining data, testing and presenting data, discussing the probabilities, regression analysis, statistical interference, forecasting and also discussing the risk factors for learning and examining all the aspects for management