statistica全套操作手册，包括数据挖掘部分！简体中文！
目录
BASIC STATISTICS AND TABLES 3
Basic Statistics and Tables--Descriptive Statistics 3
Basic Statistics and Tables--Correlation Matrices 5
Basic Statistics and Tables--t-Test, Independent, by Groups 6
Basic Statistics and Tables--t-Test for Independent Samples, by Variables 9
Basic Statistics and Tables--t-Test, Dependent samples 10
Basic Statistics and Tables--t-Test, Single Sample 12
Basic Statistics and Tables--Frequency Tables 14
Basic Statistics and Tables--Breakdown and One-Way ANOVA 16
Basic Statistics and Tables--Crosstabulation Tables 17
Basic Statistics and Tables--Stub and Banner Tables 19
MULTIPLE REGRESSION 22
Standard Multiple Regression 22
Stepwise Multiple Regression 23
ANOVA 26
Main Effects ANOVA 26
Factorial ANOVA 29
Repeated Measures ANOVA 31
NONPARAMETRICS 34
（1）Observed vs. Expected Chi-Square 34
（2）Correlations (Spearman, Kendall Tau, Gamma) 35
（3）Comparing Two Independent Samples (Groups) 37
（4）Comparing Multiple Indep. Samples (Groups) 39
（5）Comparing Two Dependent Samples (Variables) 40
（6）Comparing Multiple Dep. Samples (Variables) 42
DISTRIBUTION FITTING 45
ADVANCED LINEAR AND NONLINEAR MODELS 47
1.General Linear Models 47
2.Generalized Linear and Nonlinear Models 56
3.General Regression Models 61
4.General Partial Least Squares Models 67
5.Variance Components 71
6.Survival Analysis 73
7.Nonlinear Estimation 87
8.Log-Linear Analysis of Frequency Tables 95
9.Time Series and Forecasting 98
10.Structural Equation Modeling 138
MULTIVARIATE EXPLORATORY TECHNIQUES 142
1.Cluster Analysis 142
2.Factor Analysis 151
3.Principal Components and Classification Analysis 155
4.Canonical Correlation— 160
5.Reliability and Item Analysis 162
5.1、Reliability and Item Analysis 162
6.Classification Trees 164
7.Correspondence Analysis 170
8.Multidimensional Scaling 175
9.Discriminant Analysis 178
10.General Discriminant Analysis 183
INDUSTRIAL STATISTICS AND SIX SIGMA 191
1.Quality Control Charts 191
DATA MINING 195
1.Neural Networks 195
2.Independent Component Analysis 221
3.Generalized Cluster Analysis 224
4. General Classification And Regression Tree Models 230
5.General CHAID Models 243
6.Advanced C and RT, CHAID (using Interactive Trees) 261
7.Boosted Trees 281
8. Generalized Additive Models 286
9. MARSplines 291
10. Machine Learning 293
11.Rapid Deployment 299
12.Goodness Of Fit 301
13.Combining Groups 303