元线性回归分析估计两个变量的关 系 其中一个变量作为响应变量或输出变量 (y)o 另一个变量作为预测变量或解释变量 有时两个变量中哪一个是响应变量(例 如高度和重量)是不好区分的。在这种 情况下,可能会使用相关分析

图形的优越性 “使复杂的思想能够显示得清楚、准确、有 效。” 显示数据。 让你考虑实质而不是方法、图形设计或者其 它的。 在很小的空间中有很多的数字。 使大的数据集有条理。 使数据的不同部分显示得更清楚

S-Plus石油城市数据框架 石油的月超额回报,包含股票和市场。 SUMMARY: The oilcity data frame has 129 rows and 2 columns. The sample runs from April 1979 to December 1989. This data frame contains the following columns VALUE

预防医学 Preventive medicine 是医学的一门应用学科，以个体和确定的群体为对象，目的是保护、促进和维护健康，预防疾病、失能和夭折

How to construct various control charts Which control charts to use for a particular type of data How to measure the capability of a process The basic themes of quality management and Deming’s 14 points The basic aspects of Six Sigma

Demand Management Qualitative Forecasting Methods Time Series Analysis – Static method – Adaptive method Simple & Weighted Moving Average Forecasts Exponential Smoothing Exponential Smoothing with trend Exponential Smoothing with trend & seasonality Simple Linear Regression

To use regression analysis to predict the value of a dependent variable based on an independent variable The meaning of the regression coefficients bo and b . To evaluate the assumptions of regression analysis and know what to do if the assumptions are violated . To make inferences about the slope and correlation coefficient . To estimate mean values and predict individual values

 Recognize situations in which to use analysis of variance  Understand different analysis of variance designs  Perform a single-factor hypothesis test and interpret results  Conduct and interpret post-hoc multiple comparisons procedures  Analyze two-factor analysis of variance tests

 Test hypotheses for the difference between two independent population means (standard deviations known or unknown)  Test two means from related samples for the mean difference  Complete a Z test for the difference between two proportions  Use the F table to find critical F values  Complete an F test for the difference between two variances

 Formulate null (H0) and alternative hypotheses (H1) for applications involving one sample population mean or proportion  Formulate a decision rule for testing a hypothesis  Know how to use the critical value and p-value approaches to test the null hypothesis (for both mean and proportion problems)  Know what Type I and Type II errors are