第二节 率的u检验 第三节 卡方检验 第四节 四格表确切概率法 第一节 率的抽样误差与区间估计

第五节 常用的相对数指标 第二节 应用相对数应注意的问题 第三节 率的标准化法 第四节 动态数列及其分析指标 第一节 常用相对数

第五节 多个方差齐性检验 第二节 单因素方差分析 第三节 双因素方差分析 第四节 多个样本均数间两两比较 第一节 方差分析的基本思路 第六节 变量变换

第五节 均数的u检验 第二节 t分布 第三节 总体均数的区间估计 第四节 假设检验的意义和基本步骤 第一节 均数的抽样误差与标准误 第六节 均数的t检验 第七节 方差齐性检验和校正检验 第八节 第一类和第二类错误 第九节 应用假设检验注意问题

◆第一节 频数分布 ◆第三节 离散趋势的描述 ◆第四节 正态分布 ◆第二节 集中趋势的描述

To describe the properties of central tendency, variation and shape in numerical data To calculate descriptive summary measures for a population To construct and interpret a box-and-whisker plot To describe the covariance and coefficient of correlation as a measure of the strength of the relationship between two numerical variables

▪ Interpret the mean and standard deviation for a discrete probability distribution ▪ Explain covariance and its application in finance ▪ Use the binomial probability distribution to find probabilities ▪ Describe when to apply the binomial distribution ▪ Discuss the Hypergeometric distribution ▪ Review the Poisson distribution

 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

 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

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