Titlebook: Business Statistics for Competitive Advantage with Excel and JMP ; Basics, Model Buildi Cynthia Fraser Textbook 2024 The Editor(s) (if appl

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Analytics with Simple Regression to Identify Drivers and Forecast,linear association between two variables. Regression quantifies the influence of a continuous, . on a continuous . variable .. In the case of a trend focused forecast, the driving variable . is time period. In later chapters, focus will be expanded to both explain how an independent decision variabl

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Building Multiple Regression Models,le regression. Multiple regression accounts for the joint impact of multiple drivers, which provides a truer estimate of the impact of each one individually. Looking at just one driver, as in simple regression, its estimated impact will be much greater than it actually is. A single driver takes the

Decrepit

Explanatory Time Series Models,gression models from cross sectional data do. When decision makers want to forecast . performance in the shorter term, a time series of past performance is used to identify drivers and fit a model. A time series model can be used to identify drivers whose variation over time is associated with later

Urologist

Analytics to Simulate Likely Outcomes, values. To estimate future performance, managers make assumptions about likely future scenarios and uncertain future values of performance drivers. . can be used to simulate random samples using decision makers’ assumptions about performance driver values, and those random samples can then be combi

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Business Statistics for Competitive Advantage with Excel and JMP 978-3-031-42555-4

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f inference, Monte Carlo simulation, contingency analysis, and linear and nonlinear regression. A new chapter is dedicated to conjoint analysis design and analysis, including complementary use of regression and978-3-031-42557-8978-3-031-42555-4