医药应用统计学

Introduction Ⅰ. The History of Statistics Development Ⅱ. Introduction to Common Statistical SoftwareChapter 1 Description and Processing of Data Section 1 Type and Processing of Data Ⅰ. Classification of Data Ⅱ. Data Statistical Processing and Graphic Section 2 Statistical Description of Data Distribution Characteristics Ⅰ. Description of Central Tendency of Data Distribution Ⅱ. Description of Dispersion of Data Distribution Ⅲ. Description of the Data Distribution Shape Section 3 Intuitive Description of Data: Statistical Charts Ⅰ. Statistical Graph Ⅱ. Statistical Table Comprehensive Exercise OneChapter 2 Random Event and Probability Section 1 Random Events and Their Probability Ⅰ. Random Experiment and Random Event Ⅱ. The Relationships among Events and Their Calculations Ⅲ. Event Probability Section 2 Properties of Probability and Its Operation Rules Ⅰ. Addition Law of Probability Ⅱ. Conditional Probability and Multiplication Theorem Ⅲ. Independence of Events Section 3 Law of Total Probability and Bayes' Formula Ⅰ. Law of Total Probability Ⅱ, Bayes' Formula Comprehensive Exercise TwoChapter 3 Random Variables and Their Distribution Section 1 Random Variables and Their Probability Distributions Ⅰ. The Distribution of Discrete Random Variables Ⅱ. The Distribution Function of Random Variables Ⅲ. The Distribution of Continuous Random Variables Section 2 Numerical Features of Random Variables Ⅰ. Mathematical Expectation Ⅱ. Variance and Standard Deviation Ⅲ. Moments Section 3 Common Discrete Probability Distribution Ⅰ. Binomial Distribution Ⅱ. Poisson Distribution Ⅲ. Hypergeometric Distribution Section 4 Common Continuous Probability Distribution Ⅰ. Normal Distribution Ⅱ. Exponential Distribution Comprehensive Exercise ThreeChapter4 Sampling Distribution Section 1 Basic Concept of Mathematical Statistics Ⅰ. Population and Sample II. Statistics Section 2 Sampling Distribution Ⅰ. The Distribution of Sample Mean Ⅱ. χ2 Distribution Ⅲ. t-Distribution IV. F Distribution Comprehensive Exercise FourChapter5 Parameter Estimation Section 1 Point Estimation of Parameters Ⅰ. Moment Estimation Method Ⅱ. The Criterion of Good Estimator Section 2 Interval Estimation of Normal Population Parameters I. The Concept of Interval Estimation Ⅱ. Interval Estimation of Normal Population Mean Section 3 Interval Estimation of Binomial Distribution Parameters Ⅰ. 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 Ⅰ. Hypothesis Test Question Ⅱ. The Basic Principles of Hypothesis Test Ⅲ. General Steps of Hypothesis Test Ⅳ. Two Types of Errors in Hypothesis Test Section 2 Test for Normal Population Parameter with One Sample Ⅰ.Test for Mean of Normal Population with Known Variance Ⅱ. Test for Mean of Normal Population with Unknown Variance Ⅲ. Test for Variance of Normal Population Section 3 Test for Normal Population Parameters with Two Samples Ⅰ. Test for Homogeneity of Variance Ⅱ. Test for the Means with Two Independent Samples Ⅲ. Test for the Means with Two Paired Samples Comprehensive Exercise SixChapter 7 Nonparametric Hypothesis Test Section 1 χ2 Goodness-of-Fit Test Ⅰ. Ideas and Steps of χ2 Goodness-of-Fit Test Ⅱ. Application of χ2 Goodness-of-Fit Test Examples Section 2 χ2 Test of the Contingency Table Ⅰ. The 2'2 Independence Test of the Contingency Table I1. Contingency Table χ2 Test for the Comparison of the Population Rate Section 3 Rank Sum Test Ⅰ. Signed Rank Sum Test for Paired Comparison Ⅱ. Rank Sum Tests of Two Population Comparison Ⅲ. The Rank Sum Test of Multiple Population Comparisons Comprehensive Exercise SevenChapter 8 Analysis of Variance Section 1 One-Way Analysis of Variance Ⅰ. The Principle and Method of Analysis of Variance Ⅱ. Steps and Examples of Analysis of Variance Section 2 Multiple Comparisons Ⅰ. Tukey Method Ⅱ. Scheffe's Method Section 3 Examples of Two-way Analysis of Variance Comprehensive Exercise EightChapter 9 Correlation and Regression Analysis Section 1 Correlation Analysis Ⅰ. Scatter Plot Ⅱ. Correlation and Sample Correlation Coefficient Ⅲ. Spearman Correlation Analysis Section 2 Simple Linear Regression Analysis Ⅰ. Statistical Model of Simple Linear Regression Ⅱ. The Establishment of Linear Regression Equation Ⅲ. The Significance Test of Linear Regression Equation Ⅳ. Using Regression Equation to Predict and Control Ⅴ. 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 λ-Poisson Distribution Table 10 ψ=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