Component Factors of the Time-Series Model Smoothing of Data Series Moving Averages Exponential Smoothing Least Square Trend Fitting and Forecasting Linear, Quadratic and Exponential Models Autoregressive Models Choosing Appropriate Models Monthly or Quarterly Data

The Payoff Table and Decision Trees Opportunity Loss Criteria for Decision Making Expected Monetary Value Expected Profit Under Certainty Return to Risk Ratio Decision Making with Sample Information Utility

The Multiple Regression Model Contribution of Individual Independent Variables Coefficient of Determination Categorical Explanatory Variables Transformation of Variables Model Building

Types of Regression Models Determining the Simple Linear Regression Equation Measures of Variation in Regression and Correlation Assumptions of Regression and Correlation Residual Analysis and the Durbin-Watson Statistic Estimation of Predicted Values Correlation Measuring the Strength of the Association

Testing with Rank Sum Z Test for Differences in Two Proportions (Independent Samples) x2Test for Differences in Two Proportions (Independent Samples) x2Test for Differences in c Proportions (Independent Samples) x2Test of Independence

Basic Probability Concepts: Sample Spaces and Events, Simple Probability, and Joint Probability(联合概率) Conditional Probability(条件概率) Bayesian Theorem(贝叶斯定理) .The Probability of a Discrete Random Variable .Binomial, Poisson, and Hypergeometric Distributions Covariance(协方差) and its Applications in Finance

一、集中趋势(Central Tendency) 1, What is the most typical value? The Average: typical value for quantitative data The Weighted Average: Adjusting for importance The Median: typical value for quantitative and ordinal data The Mode: typical value even for nominal data 2, What percentile is it? Extremes, Quartiles, and Box Plots The Cumulative distribution function displays the percentiles

The Completely Randomized Model One-Factor Analysis of Variance F-Test for Difference in c Means The Tukey-Kramer Procedure ANOVA Assumptions The Factorial Design Model: Two-Way Analysis of Variance Examine Effect of Factors and Interaction Kruksal-Wallis Rank Test for Differences in c Medians

一、数据集合 Measurements of items e.g., Yearly sales volume for your 23 salespeople e.g., Cost and number produced, daily, for the past month 二、基本单元 The items being measured e.g., Salespeople, Days, Companies, Catalogs, . 三、变量 The type of measurement being done e.g., Sales volume, Cost, Productivity, Number of defects

一、什么是统计学?(what''s Statistics) 统计学是一门研究事物数量方面的方法论的学科。 二、什么是管理统计学?(what''s Statistics for Management) 将统计学的方法应用于管理领域,称为管理统计 学