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Introduction ¢ñ. The History of Statistics Development ¢ò. Introduction to Common Statistical SoftwareChapter 1 Description and Processing of Data Section 1 Type and Processing of Data ¢ñ. Classification of Data ¢ò. Data Statistical Processing and Graphic Section 2 Statistical Description of Data Distribution Characteristics ¢ñ. Description of Central Tendency of Data Distribution ¢ò. Description of Dispersion of Data Distribution ¢ó. Description of the Data Distribution Shape Section 3 Intuitive Description of Data: Statistical Charts ¢ñ. Statistical Graph ¢ò. Statistical Table Comprehensive Exercise OneChapter 2 Random Event and Probability Section 1 Random Events and Their Probability ¢ñ. Random Experiment and Random Event ¢ò. The Relationships among Events and Their Calculations ¢ó. Event Probability Section 2 Properties of Probability and Its Operation Rules ¢ñ. Addition Law of Probability ¢ò. Conditional Probability and Multiplication Theorem ¢ó. Independence of Events Section 3 Law of Total Probability and Bayes' Formula ¢ñ. Law of Total Probability ¢ò, Bayes' Formula Comprehensive Exercise TwoChapter 3 Random Variables and Their Distribution Section 1 Random Variables and Their Probability Distributions ¢ñ. The Distribution of Discrete Random Variables ¢ò. The Distribution Function of Random Variables ¢ó. The Distribution of Continuous Random Variables Section 2 Numerical Features of Random Variables ¢ñ. Mathematical Expectation ¢ò. Variance and Standard Deviation ¢ó. Moments Section 3 Common Discrete Probability Distribution ¢ñ. Binomial Distribution ¢ò. Poisson Distribution ¢ó. Hypergeometric Distribution Section 4 Common Continuous Probability Distribution ¢ñ. Normal Distribution ¢ò. Exponential Distribution Comprehensive Exercise ThreeChapter4 Sampling Distribution Section 1 Basic Concept of Mathematical Statistics ¢ñ. Population and Sample II. Statistics Section 2 Sampling Distribution ¢ñ. The Distribution of Sample Mean ¢ò. ¦Ö2 Distribution ¢ó. t-Distribution IV. F Distribution Comprehensive Exercise FourChapter5 Parameter Estimation Section 1 Point Estimation of Parameters ¢ñ. Moment Estimation Method ¢ò. The Criterion of Good Estimator Section 2 Interval Estimation of Normal Population Parameters I. The Concept of Interval Estimation ¢ò. Interval Estimation of Normal Population Mean Section 3 Interval Estimation of Binomial Distribution Parameters ¢ñ. 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 ¢ñ. Hypothesis Test Question ¢ò. The Basic Principles of Hypothesis Test ¢ó. General Steps of Hypothesis Test ¢ô. Two Types of Errors in Hypothesis Test Section 2 Test for Normal Population Parameter with One Sample ¢ñ.Test for Mean of Normal Population with Known Variance ¢ò. Test for Mean of Normal Population with Unknown Variance ¢ó. Test for Variance of Normal Population Section 3 Test for Normal Population Parameters with Two Samples ¢ñ. Test for Homogeneity of Variance ¢ò. Test for the Means with Two Independent Samples ¢ó. Test for the Means with Two Paired Samples Comprehensive Exercise SixChapter 7 Nonparametric Hypothesis Test Section 1 ¦Ö2 Goodness-of-Fit Test ¢ñ. Ideas and Steps of ¦Ö2 Goodness-of-Fit Test ¢ò. Application of ¦Ö2 Goodness-of-Fit Test Examples Section 2 ¦Ö2 Test of the Contingency Table ¢ñ. The 2'2 Independence Test of the Contingency Table I1. Contingency Table ¦Ö2 Test for the Comparison of the Population Rate Section 3 Rank Sum Test ¢ñ. Signed Rank Sum Test for Paired Comparison ¢ò. Rank Sum Tests of Two Population Comparison ¢ó. The Rank Sum Test of Multiple Population Comparisons Comprehensive Exercise SevenChapter 8 Analysis of Variance Section 1 One-Way Analysis of Variance ¢ñ. The Principle and Method of Analysis of Variance ¢ò. Steps and Examples of Analysis of Variance Section 2 Multiple Comparisons ¢ñ. Tukey Method ¢ò. Scheffe's Method Section 3 Examples of Two-way Analysis of Variance Comprehensive Exercise EightChapter 9 Correlation and Regression Analysis Section 1 Correlation Analysis ¢ñ. Scatter Plot ¢ò. Correlation and Sample Correlation Coefficient ¢ó. Spearman Correlation Analysis Section 2 Simple Linear Regression Analysis ¢ñ. Statistical Model of Simple Linear Regression ¢ò. The Establishment of Linear Regression Equation ¢ó. The Significance Test of Linear Regression Equation ¢ô. Using Regression Equation to Predict and Control ¢õ. 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 ¦Ë-Poisson Distribution Table 10 ¦×=2arcsin ¡ÌP 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