Introduction ��. The History of Statistics Development ��. Introduction to Common Statistical SoftwareChapter 1 Description and Processing of Data Section 1 Type and Processing of Data ��. Classification of Data ��. Data Statistical Processing and Graphic Section 2 Statistical Description of Data Distribution Characteristics ��. Description of Central Tendency of Data Distribution ��. Description of Dispersion of Data Distribution ��. Description of the Data Distribution Shape Section 3 Intuitive Description of Data: Statistical Charts ��. Statistical Graph ��. Statistical Table Comprehensive Exercise OneChapter 2 Random Event and Probability Section 1 Random Events and Their Probability ��. Random Experiment and Random Event ��. The Relationships among Events and Their Calculations ��. Event Probability Section 2 Properties of Probability and Its Operation Rules ��. Addition Law of Probability ��. Conditional Probability and Multiplication Theorem ��. Independence of Events Section 3 Law of Total Probability and Bayes' Formula ��. Law of Total Probability ��, Bayes' Formula Comprehensive Exercise TwoChapter 3 Random Variables and Their Distribution Section 1 Random Variables and Their Probability Distributions ��. The Distribution of Discrete Random Variables ��. The Distribution Function of Random Variables ��. The Distribution of Continuous Random Variables Section 2 Numerical Features of Random Variables ��. Mathematical Expectation ��. Variance and Standard Deviation ��. Moments Section 3 Common Discrete Probability Distribution ��. Binomial Distribution ��. Poisson Distribution ��. Hypergeometric Distribution Section 4 Common Continuous Probability Distribution ��. Normal Distribution ��. Exponential Distribution Comprehensive Exercise ThreeChapter4 Sampling Distribution Section 1 Basic Concept of Mathematical Statistics ��. Population and Sample II. Statistics Section 2 Sampling Distribution ��. The Distribution of Sample Mean ��. ��2 Distribution ��. t-Distribution IV. F Distribution Comprehensive Exercise FourChapter5 Parameter Estimation Section 1 Point Estimation of Parameters ��. Moment Estimation Method ��. The Criterion of Good Estimator Section 2 Interval Estimation of Normal Population Parameters I. The Concept of Interval Estimation ��. Interval Estimation of Normal Population Mean Section 3 Interval Estimation of Binomial Distribution Parameters ��. Normal Approximation Method for Large Samples 11. Exacted Estimation Method for Small Samples Comprehensive Exercise FiveChapter 6 Parameter Hypothesis Test Section 1 Introduction to Hypothesis Test ��. Hypothesis Test Question ��. The Basic Principles of Hypothesis Test ��. General Steps of Hypothesis Test ��. Two Types of Errors in Hypothesis Test Section 2 Test for Normal Population Parameter with One Sample ��.Test for Mean of Normal Population with Known Variance ��. Test for Mean of Normal Population with Unknown Variance ��. Test for Variance of Normal Population Section 3 Test for Normal Population Parameters with Two Samples ��. Test for Homogeneity of Variance ��. Test for the Means with Two Independent Samples ��. Test for the Means with Two Paired Samples Comprehensive Exercise SixChapter 7 Nonparametric Hypothesis Test Section 1 ��2 Goodness-of-Fit Test ��. Ideas and Steps of ��2 Goodness-of-Fit Test ��. Application of ��2 Goodness-of-Fit Test Examples Section 2 ��2 Test of the Contingency Table ��. The 2'2 Independence Test of the Contingency Table I1. Contingency Table ��2 Test for the Comparison of the Population Rate Section 3 Rank Sum Test ��. Signed Rank Sum Test for Paired Comparison ��. Rank Sum Tests of Two Population Comparison ��. The Rank Sum Test of Multiple Population Comparisons Comprehensive Exercise SevenChapter 8 Analysis of Variance Section 1 One-Way Analysis of Variance ��. The Principle and Method of Analysis of Variance ��. Steps and Examples of Analysis of Variance Section 2 Multiple Comparisons ��. Tukey Method ��. Scheffe's Method Section 3 Examples of Two-way Analysis of Variance Comprehensive Exercise EightChapter 9 Correlation and Regression Analysis Section 1 Correlation Analysis ��. Scatter Plot ��. Correlation and Sample Correlation Coefficient ��. Spearman Correlation Analysis Section 2 Simple Linear Regression Analysis ��. Statistical Model of Simple Linear Regression ��. The Establishment of Linear Regression Equation ��. The Significance Test of Linear Regression Equation ��. Using Regression Equation to Predict and Control ��. Simple Quasi-linear Regression Analysis Section 3 Sample of Multiple Linear Regression Analysis Comprehensive Exercise NineReferenceAppendix Tables Table 1 Cumulative Binomial Probabilities Table 2 Cumulative Poisson Probabilities Table 3 The Standard Normal Distribution Table 4 Two-tailed critical Values for Standard Normal Distribution Table 5 Critical Values for Chi-square Distribution Table 6 Critical Values for t Distribution Table 7 Critical Values for F Distribution Table 8 Confidence Interval for p-Binomial Distribution Table 9 Confidence Interval for ��-Poisson Distribution Table 10 ��=2arcsin ��P Table 11 Critical Values for the T Test Statistic for Signed Rank Sum Test for Paired Comparison Table 12 Critical Values for the T Test Statistic for Rank Sum Test for Two Populations Comparison Table 13 Critical Values for the Kruskal-Wallis Test Statistic (H) for Selected Sample Sizes for k=3 Table 14 Critical Values for the Studentized Range Statistic q Table 15 Critical Values for the Studentized Range Statistic S Table 16 Critical Value for the Correlation Coefficient Table 17 Critical Values for Coefficient of Rank Correlation