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# Chapter 12 Enhancing Decision Making Which of the following statements best describes the business value of improved decision making at all levels of a firm? Improved decision making creates better products. Improved decision making results in a large monetary value for the firm as numerous...
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# Chapter 11 Managing Knowledge and Artificial Intelligence Which of the following is the first value-adding step of information system activities in the knowledge management value chain? Feedback Acquire Disseminate Store Apply Which of the following involves where, when, and how to apply...
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# Chapter 9 Achieving Operational Excellence and Customer Intimacy: Enterprise Applications From your reading of the chapter's opening case, which of the answers below is not a reason why Lenzing chose JDA's Sales & Operations Planning software? Minimize the environmental impact of...
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# Chapter 2 Global E-business and Collaboration Producing a bill of materials is a business process in which of the following functional areas? Finance and accounting Human resources Manufacturing and production Research and development Sales and marketing Which of the following is an example of...
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# Chapter 1 Information Systems in Global Business Today Which of the following is not one of the six strategic business objectives that businesses are seeking to achieve when they invest in information systems? Operational excellence Improved decision making Improved community...
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# 相关 vs. 回归 相关分析 用来度量两个变量之间线性关系的强度 相关只考虑相关关系的强度 相关关系中不涉及因果关系 回归分析 根据至少一个自变量的值预测因变量的值 解释自变量的变化对因变量的影响 因变量 Dependent variable : 我们希望预测或解释的变量 自变量 Independent variable : 用来预测或解释因变量的变量 # 简单线性回归模型 只有一个自变量 XXX 用线性函数来描述 XXX 与 YYY 之间的关系 假定 YYY 的变化与 XXX 的变化相关 # 模型与假设 线性模型 Yi=β0+β1Xi+ϵiY_i = \beta_0...
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# 单因素方差分析 只有一个因素或因变量,有 2 个或多个水平,用单因素方差分析进行分析 假设: 总体服从正态分布 不同总体有相同的方差 样本随机、独立抽取 假设 H0:μ1=μ2=μ3=⋯=μcH_0: \mu_1 =\mu_2 =\mu_3 = \cdots = \mu_cH0​:μ1​=μ2​=μ3​=⋯=μc​ 所有样本均值都相等 即,没有因素效果 (不同组的均值没有变化) 假设 H1:Not all μj are the sameH_1: Not\ all\ \mu_j\ are\...
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# 均值检验 # 相互独立样本 # σ1\sigma_1σ1​ 与 σ2\sigma_2σ2​ 未知,假设相等 用 SpS_pSp​ 估计未知的 σ\sigmaσ. 使用混合方差 t 检验 Pooled-variance t-test 假设检验 Lower-tail test: H0:μ1−μ2≥0,H1:μ1−μ2<0H_0: \mu_1 - \mu_2 \ge 0, H_1: \mu_1 - \mu_2 <...
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# 假设检验基础 假设是关于总体参数的声明或断言 # 零假设 (原假设) H0H_0H0​ 假设检验从假定零假设为真开始. 零假设表示现状或历史值 包含 === , ≤\leq≤ 或 ≥\geq≥ 符号 可能会或不会被拒绝 例:美国家庭平均拥有的电视机数量等于 3 H0:μ=3H_0: \mu = 3H0​:μ=3 注意: 是关于总体参数,而不是样本参数, 即,不是 H0:X‾=3H_0: \overline{X} = 3H0​:X=3 # 备择假设 H1H_1H1​ 与零假设是对立的 永远不包含 === , ≤\leq≤ 或 ≥\geq≥...