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標(biāo)題: Titlebook: Business Statistics for Competitive Advantage with Excel and JMP ; Basics, Model Buildi Cynthia Fraser Textbook 2024 The Editor(s) (if appl [打印本頁]

作者: 憑票入場    時(shí)間: 2025-3-21 20:03
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作者: 盡管    時(shí)間: 2025-3-21 22:32
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
作者: Interstellar    時(shí)間: 2025-3-22 01:22

作者: 褪色    時(shí)間: 2025-3-22 06:08
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
作者: Decrepit    時(shí)間: 2025-3-22 09:04
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
作者: Urologist    時(shí)間: 2025-3-22 15:12
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
作者: 圓錐體    時(shí)間: 2025-3-22 19:56

作者: 評論性    時(shí)間: 2025-3-22 21:22

作者: 設(shè)施    時(shí)間: 2025-3-23 01:31
Business Statistics for Competitive Advantage with Excel and JMP 978-3-031-42555-4
作者: 人造    時(shí)間: 2025-3-23 08:16
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
作者: 混亂生活    時(shí)間: 2025-3-23 13:42

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作者: 針葉類的樹    時(shí)間: 2025-3-24 18:37
Medizinische Begutachtung für Einsteiger can be used to simulate random samples using decision makers’ assumptions about performance driver values, and those random samples can then be combined to produce a distribution of likely future outcomes. Inferences from a simulated distribution of outcomes, given assumptions, can then be made to inform decision making and to adjust assumptions.
作者: GROSS    時(shí)間: 2025-3-24 21:14
Analytics to Infer Population Characteristics and Differences,ers are estimated with .. Included in this chapter are tests of hypotheses and confidence intervals forInference relies on the properties of Normally distributed sample means. Those properties of Normal distributions are explored first, below.
作者: HERTZ    時(shí)間: 2025-3-25 02:54

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作者: Palter    時(shí)間: 2025-3-25 20:41
In-vitro-Testung von Chemotherapeutika,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
作者: Cardioversion    時(shí)間: 2025-3-26 00:53
Besonderheiten in den Fachgebietengression 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
作者: NEEDY    時(shí)間: 2025-3-26 06:17
Medizinische Begutachtung für Einsteiger 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
作者: 確定的事    時(shí)間: 2025-3-26 08:36

作者: nitric-oxide    時(shí)間: 2025-3-26 13:43

作者: Bother    時(shí)間: 2025-3-26 18:33

作者: 管理員    時(shí)間: 2025-3-26 22:28

作者: 無意    時(shí)間: 2025-3-27 04:00

作者: Urea508    時(shí)間: 2025-3-27 05:58

作者: 紅腫    時(shí)間: 2025-3-27 10:08
https://doi.org/10.1007/978-3-642-75404-3In many cases, trends (and other responses) are not constant over time periods. To accommodate nonlinear response, variables can be rescaled to produce valid models with superior fit. An example will be offered in the context of trend models built for forecasting.
作者: SHRIK    時(shí)間: 2025-3-27 14:14

作者: 臥虎藏龍    時(shí)間: 2025-3-27 20:15
Analytics for Description,All analytics begin with data. The type of analytics depends on the type of data. In this chapter, we look at types of data, ways to display data graphically, and means to describe data.
作者: 防水    時(shí)間: 2025-3-28 01:22
Finance Application: Portfolio Analysis with a Market Index as a Leading Indicator in Simple LinearSimple linear regression of stock rates of return with a Market index provides an estimate of ., a measure of Market specific risk, which is central to finance investment theory.
作者: 下船    時(shí)間: 2025-3-28 04:56

作者: 蔑視    時(shí)間: 2025-3-28 10:00

作者: CHURL    時(shí)間: 2025-3-28 12:25

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作者: 表狀態(tài)    時(shí)間: 2025-3-28 20:04
Analytics to Account for Segment or Scenario Differences,tional data, indicators can be used to incorporate the unique responses of particular groups or segments. With time series data, indicators can be used to account for external shocks or structural shifts. Indicators also offer one option to account for seasonality or cyclicality in time series.
作者: JAUNT    時(shí)間: 2025-3-29 01:24
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 variation in performance over time.
作者: 暖昧關(guān)系    時(shí)間: 2025-3-29 06:30
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作者: bizarre    時(shí)間: 2025-3-29 09:54
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