THE CHAPTER THIS WEEK FOCUSES ON \"Cost Volume Profit (CVP)\". For purposes of C
ID: 2550443 • Letter: T
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THE CHAPTER THIS WEEK FOCUSES ON "Cost Volume Profit (CVP)". For purposes of CVP Analysis, it is assumed that certain cost characteristics are valid within the "Relevant Range" Mixed costs present an issue in determining what portion of such a cost is fixed and which is variable The chapter presents a graph method and a high-low method of separating the fixed and variable portions of mixed costs. The Least-Squares Regression Method is considered to be the most accurate and is covered in other text ooks on Managerial Accounting. It can be easily calculated with excel or by using a formula. Do a little research on the Least-Squares Method. Briefly discuss (in your own words) why the Least-Squares Method would be the best of the three methods. There is no precise answer. it isExplanation / Answer
The least squares method is a form of mathematical regression analysis that finds the line of best fit for a dataset, providing a visual demonstration of the relationship between the data points. Each point of data is representative of the relationship between a known independent variable and an unknown dependent variable.
The most important application is in data fitting. The best fit in the least-squares sense minimizes the sum of squared residuals (a residual being: the difference between an observed value, and the fitted value provided by a model). When the problem has substantial uncertainties in the independent variable (the x variable), then simple regression and least-squares methods have problems; in such cases, the methodology required for fitting errors-in-variables modelsmay be considered instead of that for least squares.
Least-squares problems fall into two categories: linear or ordinary least squaresand nonlinear least squares, depending on whether or not the residuals are linear in all unknowns. The linear least-squares problem occurs in statistical regression analysis; it has a closed-form solution. The nonlinear problem is usually solved by iterative refinement; at each iteration the system is approximated by a linear one, and thus the core calculation is similar in both cases.
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