Introduction to 1. 1SPSS

Installation, startup and exit of 1.2 PSS

Install1.2.1SPSS15.0.

1. 2. 2 seconds.

1.2.3 Exit from SPSS 15.0.

Interface and settings of 1.3 PSS 15.0

1.3. 1

1.3.2 General functional parameters

1. 3. 3 Viewer View Window Parameters

1.3.4DraftViewer parameter

1. 3. 5 output label output label parameters

1. 3. 6 Chart graphic parameters

1. 3. 7 interactive interactive graphic window parameters

1. 3. 8 Pivot Table Pivot Table Parameters

1. 3. 9 data data parameters

1. 3. 10 format parameters of currency numerical variables

1.3. 1 script script editing window

Chapter II Establishment and Operation of Data Files

2. 1 data editor and data file

2. 1. 1 data editor

2. 1.2 data file

2.2 Constants, Variables, Operators and Expressions

2.2. 1 constants and variables

Operators and expressions

2.2.3 How to define variables

probability event

2.3 input data

2.3. 1 data input method

2.3.2 View file information and variable information.

2.4 Edit data file

2.4. 1 Edit the data in the cell

Insert variables and delete variables

2.4.3 Insert observation and delete observation.

2.4.4 Data cutting, copying and pasting

Undo operation

2.5 Operation on data files

2.5. 1 Opening and saving of data files

Conversion of database files

Chapter III Operation of Data Files

3. 1 General operation of data file

3. 1. 1 data sorting

3. 1.2 Grouping of data files

3. 1.3 data file merging

3. 1.4 Transposition of data files

3. 1.5 Rank of variable value

3. 1.6 Re-coding of variable values

3. 1.7 Calculating new variables

3.2 Classification and summary

3.2. 1 data description

3.2.2 Classification and Summary Parameter Settings

3.2.3 classified summary results

3.3 observation weighting

3.4 data file reorganization

3.4. 1 Select the data reorganization method.

3.4.2 Reorganization from Variable Group to Observation Group

3.4.3 Reorganization from Observation Group to Variable Group

3.4.4 Transposition and reorganization

Chapter 4 Basic Statistical Analysis Functions

4. 1OLAP online analysis process

4. 1. 1 data description

4.1.2 Overlapping operation and setting of OLAP process

4.2 Observation and analysis of summary report

4.2. 1 observation summary analysis parameter setting

Output result

4.3 Row and column analysis of summary report

4.3. 1 line summary report

4.3.2 Summary report in the form of histogram

4.4 Frequency analysis

4.4. 1 data description

4.4.2 Frequency analysis of classified variables

4.4.3 Frequency analysis of continuous variables

4.5 Descriptive statistical analysis

4.5. 1 data description

Descriptive analysis

4.6 Exploration and analysis process

4.6. 1 data description

Explore case analysis

4.7 contingency table analysis process

6.5438+0 data description

4.7.2 Parameter setting of contingency table analysis

4.7.3 Output result of contingency table analysis

Chapter 5 Mean Comparison and T Test

5. 1 means process

5. The principle and method of1.1

5. 1.2 psss case study

5.2 single sample t test

5.2. 1 Principles and methods

5. 2. 2 psss case analysis

5.3 T-test of two independent samples

5.3. 1 Principles and methods

5. 3. 2 psss case analysis

5.4 paired sample t test

5.4. 1 Principles and methods

5. 4. 2 psss case analysis

Chapter 6 nonparametric test

6. 1 introduction to nonparametric test

6. 1. 1 nonparametric test and parametric test

6. 1.2 Advantages of nonparametric test

6. 1.3 Disadvantages of nonparametric test

6.2 chi-square test

6.2. 1 Principles and methods

Data and problem description

6.2.3 Chi-square test case analysis

6.3 Binomial Test

6.3. 1 Principles and methods

Data and problem description

6.3.3 Example Analysis of Binomial Test

6.4 run-length test

6.4. 1 Principles and methods

Data and problem description

6.4.3 Example Analysis of Run-length Test

6.5 Kolmogorov-smirnoff Single Sample Test

6.5. 1 Principles and methods

Data and problem description

6.5.3K-S single sample test case analysis

6.6 Two independent sample tests

6.6. 1 Principles and methods

Data and problem description

6.6.3 Analysis of Two Independent Samples

Inspection of 6.7k independent samples

6.7. 1 Principles and methods

Data and problem description

6. 7. 3 Analysis of Independent Sample Test Cases

6.8 Inspection of Two Related Samples

6.8. 1 Principles and methods

Data and problem description

6.8.3 Example Analysis of Two Related Sample Tests

Testing of 6.9k related samples

6.9. 1 Principles and methods

Data and problem description

6.9.3k Related Sample Test Case Analysis

Chapter 7 Multiple Response Analysis

7. 1 Overview of multiple responses

7.2 Definition of Multiple Response Variable Set

7.2. 1 defines an example of multiple response variable set.

7.3 Frequency analysis of multi-response variable sets

7.3. 1 frequency analysis example of multiple response variables

7.4 Cross-table analysis of multiple response variable sets

An example of crosstab analysis of multiple response variables

7.5 Using tabular process to study multiple response variable sets

7.5. Definition of1Multiple Response Variable Set

7.5.2 Create a table with multiple response variable sets by using the table process.

Chapter VIII Regression Analysis

8. 1 linear regression

8. 1. 1 Basic principle of linear regression with one variable

8. 1.2 Basic principles of multiple linear regression

8. Other tests of the hypothesis of1.3 model

8. 1.4 problem description and data preparation

8. 1.5 Setup and operation of linear regression analysis

8. 1.6 case result analysis

8.2 Curve regression

8.2. 1 Basic principle of curve regression

8.2.2 Problem Description and Data Preparation

8.2.3 Setting and Operation of Curve Regression Analysis

8.2.4 Case result analysis

8.3 nonlinear regression

8.3. 1 Introduction to Nonlinear Regression

8.3.2 Problem Description and Data Preparation

8.3.3 nonlinear regression parameter setting

8.3.4 Case result analysis

8.4 Binary logistic regression

8.4. Mathematical principle of1binary logic regression

8.4.2 Problem Description and Data Preparation

8.4.3 Parameter setting of binary logistic regression

8.4.4 Case result analysis

8.5 Multiple logistic regression analysis

8.5. 1 Brief introduction to the principle of multiple logistic regression

8.5.2 Problem Description and Data Preparation

8.5.3 Parameter setting of multiple logistic regression

8.5.4 Case result analysis

8.6 ordinal regression

8.6. 1 problem description and data preparation

8.6.2 Parameter Setting of Ordered Regression

8.6.3 Analysis of Case Results

8.7 Probability unit regression analysis

8.7. 1 Brief Introduction of Probabilistic Unit Regression Analysis

8.7.2 Problem Description and Data Preparation

8.7.3 Parameter Setting of Probability Unit Regression

8.7.4 Case result analysis

8.8 Weighted regression analysis

8.8. 1 introduction to weighted regression analysis

8.8.2 Problem Description and Data Preparation

8.8.3 Parameter setting of weighted regression

8.8.4 Analysis of Case Results

8.9 Two-stage Least Squares Regression

8.9. 1 Basic principle of two-stage least squares regression

8.9.2 Problem Description and Data Preparation

8.9.3 Parameter setting of two-stage least squares regression

8.9.4 Case result analysis

8. 10 optimal proportional regression

8. 10. 1 optimal scale regression principle

8. 10.2 problem description and data preparation

8. 10.3 parameter setting of optimal scale regression

8. 10.4 case analysis

Chapter 9 Analysis of Variance

9. Introduction to1ANOVA

9. Comparison between1.1t test and analysis of variance

9. 1.2 Basic principle of variance analysis

9.2 One-way ANOVA

9.2. 1 Principles and methods

9.2.2 One-way ANOVA Example

9.3 Multi-factor difference analysis process

9.3. 1 Principles and methods

9.3.2 Two-factor analysis of variance example

9.3.3 Example of Covariance Analysis

9.3.4 Analysis of Random Factors in Interaction Effect

9.4 multivariate analysis of variance

9.4. 1 Principles and methods

9.4.2 Examples of multivariate analysis of variance

9.5 Variance analysis of repeated measurement design

9.5. 1 Principles and methods

9. 5. 2 psss case analysis

9.6 Difference component analysis

9.6. 1 Principle introduction

9. 6. 2 psss case analysis

9.7 Orthogonal experimental design

9.7. 1 orthogonal experimental design

9. 7. 2 psss case analysis

9.7.3 Analysis of variance of orthogonal experimental design

Chapter 10 Association Analysis

10. 1 Basic concepts of correlation analysis

Characteristics and application of 10. 1. 1 correlation analysis

Calculation of correlation coefficient 10. 1.2

Related analysis functions provided by SPSS+00. 1.3

10.2 binary correlation analysis

10.2. 1 problem description and data preparation

10.2.2 related analysis parameter settings

10.2.3 case result analysis

10.3 partial correlation analysis

Basic principle of partial correlation analysis 10.3. 1

10.3.2 partial correlation analysis example

10.4 distance analysis

10.4. 1 Basic concepts of distance analysis

10.4.2 distance analysis parameter setting

10.4.3 distance analysis example

Chapter 1 1 Factor Analysis

1 1. 1 Brief introduction to the principle of factor analysis.

1 1. 1 the basic idea of factor analysis

1 1. 1.2 the relationship between factor analysis and principal component analysis

1 1. 1.3 Basic steps of factor analysis

1 1.2SPSS factor analysis application example

1 1.2. 1 data description

1 1. 2. 2 SPSS factor analysis process settings

1 1.2.3 result analysis

Chapter 12 classification analysis

12. 1 Brief introduction of cluster analysis principle

12. 1. 1 Basic concepts of cluster analysis

General principles of 12. 1.2 cluster analysis

12.2 fast sample clustering process

12.2. 1 Introduction to Fast Clustering

12.2.2 problem description and data preparation

12.2.3SPSS Fast Clustering Settings

12.2.4 case result analysis

12.3 hierarchical clustering

12.3. 1 Introduction to hierarchical clustering

12.3.2 problem description and data preparation

12.3.3SPSS settings for hierarchical clustering of SPSS.

12.3.4 case result analysis

Further analysis of 12.3.5 clustering results

12.4 two-stage cluster analysis

12.4. 1 introduction to two-stage clustering

12.4.2 problem description and data preparation

12.4.3SPSS two-stage clustering setting

12.4.4 case result analysis

12.5 general discriminant analysis

12.5. 1 Basic principle of discriminant analysis

12.5.2 problem description and data preparation

12.5.3 parameter setting of discriminant analysis

12.5.4 case result analysis

12.6 example of stepwise discriminant analysis

12.6. 1 problem description and data preparation

12.6.2 parameter setting for step-by-step discrimination

12.6.3 case result analysis

12.7 decision tree analysis

12.7. 1 Basic principles of decision tree classification

12.7.2 decision tree process parameter setting

12.7.3 problem description and data preparation

12.7.4 case analysis

Chapter 13 survival analysis

13. 1 Introduction to Survival Analysis

13. 1. 1 Basic concepts of survival analysis

13. 1.2 data characteristics of survival analysis

13. 1.3 Common methods of survival analysis

13.1.4 survival analysis process in SPSS.

13.2 life table analysis

Life table analysis 13.2. 1

13.2.2 Basic steps of life table analysis

13.2.3 life table case analysis

Kaplan-Meyer analysis of 13.3

13. 3. 1 Kaplan-Meyer analysis steps

Comparison and test of 13.3.2 survival curve

Kaplan-Meyer analysis example

13.4Cox regression model

Brief introduction to the principle of 13.4. 1Cox regression model

13.4.2Cox regression case analysis

Chapter 14 Reliability Analysis

Reliability analysis of 14. 1

14. 1. 1 Basic principles of reliability analysis

14. 1.2 problem description and data preparation

14. 1.3 parameter setting for reliability analysis

The result analysis of 14. 1.4 case

14.2 multidimensional scaling analysis

14.2. 1 introduction to multidimensional scaling analysis

14.2.2 problem description and data preparation

14.2.3ALSCAL parameter setting of ALSCAL process

14.2.4 case result analysis

Chapter 15 time series analysis

15.1SPSS15 time series analysis

15. 1. 1 General setting options for creating models

15. 1.2 General setting options for application models.

15.2 Pre-analysis of Time Series Data

15.2. 1 missing value replacement

15.2.2 define time variables.

15.2.3 stability of time series

15.3 exponential smoothing model

The basic principle of exponential smoothing of 15.3. 1

15.3.2 parameter setting of exponential smoothing model

15.3.3 example analysis of exponential smoothing model

15.4ARIMA model

The basic principle of 15.4. 1ARIMA model

15.4.2ARIMA parameter setting of ARIMA model

ARIMA 15. 4. 3 ARIMA Case Analysis

15.5 seasonal decomposition model

15.5. 1 Overview of seasonal decomposition method

15.5.2 Case Analysis of Seasonal Decomposition Model

Chapter 16 Logarithmic Linear Model

16. 1 Overview of Logarithmic Linear Model

Shortcomings of simple contingency table analysis of 16. 1. 1

The basic form of loglinear model 16. 1.2

16.2 general process

16. 2. 1 general process overview

16.2.2 problem description and data preparation

16. 2. 3 general process parameter setting

16.2.4 case result analysis

16.3 logic process

16. 3. 1 Overview of login process

16.3.2 problem description and data preparation

16.3.3Logit parameter setting of Logit process

16.3.4 case result analysis

16.4 model selection process

16.4. 1 model selection process overview

16.4.2 problem description and data preparation

16.4.3 operation process of hierarchical log-linear model

16.4.4 case result analysis

Chapter 17 correspondence analysis

17. 1 Basic principle of correspondence analysis

Correspondence analysis and factor analysis of 17. 1. 1

Correspondence analysis in 17. 1.2SPSS

17. 1.3 precautions in using correspondence analysis

17.2 simple correspondence analysis

17.2. 1 Mathematical principle of simple correspondence analysis

17.2.2SPSS Simple Correspondence Analysis Example

17.3 multivariate correspondence analysis

17.3. 1 Basic concepts and characteristics of multivariate correspondence analysis

17.3.2 parameter setting of multivariate correspondence analysis

17.3.3 example result analysis

Chapter 18 Missing Value Analysis

Analysis of concept missing value of 18. 1

18. 1. 1 expression with missing value

18.10.2 Processing Method of Missing Values in SPSS

18.2 parameter setting for missing value analysis

18.3 Example of missing value analysis

Chapter 19 Statistical Graphics

19. 1 overview

19. 1. 1 data and variable preparation

19. 1.2 Basic operation of the graphic generator

19. 1.3 interactive drawing and dialog drawing

19. 1.4 graphic editing

19.2 bar chart

19.2. 1 data and problem description

Use the graph generator to make a bar graph.

19.2.3 interactive bar chart

19.2.4 Create a bar chart with a dialog box.

19.3 line chart

19.3. 1 data and problem description

Make a line chart with a graph generator.

19.3.3 interactive diagram

19.3.4 Create a line chart with a dialog box.

Area diagram of 19.4

19.4. 1 data and problem description

19.4.2 Use the graphic generator to draw the regional map.

19.4.3 interactive area map

19.4.4 Create an area map with a dialog box.

19.5 pie chart

19.5. 1 data and problem description

19.5.2 Making Pie Chart with Graphic Generator

19.5.3 Interactive Pie Chart

19.5.4 Create a pie chart using a dialog box.

19.6 high and low point map

19.6. 1 data and problem description

19.6.2 Use the graphic generator to make the height map.

19.6.3 interactive height map

19.6.4 Create high-low point map with dialog box.

19.7 Pareto diagram

19.7. 1 data and problem description

19.7.2 Create Pareto Diagram with Dialog Box

19.8 control chart

19.8. 1 data and problem description

19.8.2 Create control chart with dialog box.

19.9 box diagram

19.9. 1 data and problem description

Make a block diagram with a graphic generator.

19.9.3 interactive block diagram

19.9.4 Create a block diagram with a dialog box.

19. 10 error bar chart

19. 10. 1 data and problem description

19. 10.2 interactive error bar chart

19. 10.3 Create an error bar chart with a dialog box.

19. 1 1 scatter plot

19.11.1data and problem description

19. 1 1.2 Use the graphic generator to draw the height map.

19. 1 1.3 interactive scatter plot

19. 1 1.4 Create a scatter plot with a dialog box.

19. 12 histogram

19. 12. 1 data and problem description

19. 12.2 histogram with graph generator

19. 13P-P probability diagram

19. 13. 1 data and problem description

19. 13.2 Create PAPP-P Probability Diagram with Dialog Box.

19. 14Q-Q probability diagram

19. 14. 1 data and problem description

19. 14.2 Create Q-Q probability diagram with dialog box.

19. 15 timing diagram

19. 15. 1 general sequence diagram

19. 15.2 autocorrelation sequence diagram

19. 15.3 cross-correlation sequence diagram

19. 16 biaxial graph

19. 16. 1 data and problem description

19. 16.2 Use the graphic generator for biaxial drawing.

Chapter 20 Financial Crisis Early Warning Analysis of Listed Companies

20. 1 financial crisis early warning application introduction

20. 1. 1 quantitative definition method of financial crisis

20. 1.2 model selection of financial crisis early warning

20.2 data description

20.2. 1 data description

Index selection

additional remarks

20.3 Overview of analytical methods

20.3. 1 discriminant analysis

Logical regression method

20.4SPSS modeling process and conclusion analysis

SPSS data filtering operation

20. 4. 2 psss discriminant analysis modeling and analysis

20. 4. 3 Logistic regression modeling and analysis

20.5 Further analysis and application

20.5. 1 Application analysis of classification results

20.5.2 Improvement of modeling method

20.6 Suggestions and promotion

20.6. 1 time series research

20.6.2 Data of effective early warning period

20.6.3 Simplified index method

Chapter 2 1 Analysis of Factors Affecting Exchange Rate

2 1. 1 Brief introduction of exchange rate influencing factors

2 1.2 data description

2 1.3 Analysis Method Overview

Exploratory analysis of 2 1.3. 1

2 1.3.2 multiple regression analysis

2 1.4SPSS modeling process and conclusion analysis

2 1.4. 1 data preparation

2 1.4.2 exploratory analysis

2 1.4.3 multiple regression analysis

Further analysis and application of 2 1.5

2 1.5. 1 Excluding * * * linear foreign exchange reserve variables.

Further improvement of 2 1.5.2 regression model

2 1.5.3 Comparison of Two Regression Models

2 1.6 suggestion and popularization

2 1.6. 1 time series research

2 1.6.2 qualitative analysis of influencing factors of exchange rate

Chapter 22 Application of Factor Analysis in Comprehensive Performance Evaluation

22. 1 Brief Introduction to Comprehensive Evaluation of Students' Achievements

22.2 data description

22.3 Overview of analytical methods

22.3. 1 Steps of applying factor analysis to comprehensively evaluate scores

22.3.2 Matters needing attention in applying factor score method to comprehensive performance evaluation

22.4SPSS modeling process and conclusion analysis

22.4. 1 data preparation

22. 4. 2 PSS factor analysis modeling and analysis

22.5 Further analysis and application

22.6 Suggestions and promotion

22.6. 1 Comprehensive evaluation of senior high school students' performance

Treatment of missing data

22.6.3 Comprehensive evaluation model combining multiple methods

Chapter 23 Cluster Analysis of Higher Education Conditions

23. 1 data description

23. 1. 1 Judging whether the basic conditions for running a school are qualified or not

23. 1.2 index selection

23. 1.3 data format

23.2 Introduction to Cluster Analysis

23.3SPSS modeling process and conclusion analysis

23.3. 1 university cluster setting operation

23.3.2 Analysis of Undergraduate Colleges and Universities

23.4 Suggestions and promotion

Chapter 24 Testing and Analysis of Test Paper Reliability

24. 1 Brief introduction to the background of test paper reliability test

24. 1. 1 aspects of the test content itself

24. 1.2 measurement process

24. 1.3 examinee's own factors

24.2 data description

24.3 Overview of analytical methods

24.3. 1 Basic calculation formula of test paper reliability

24.3.2 Estimation method of test paper reliability

24.4SPSS modeling process and conclusion analysis

24.4. Parameter setting of1SPSS reliability analysis

24.4.2 Analysis of results

24.5 Suggestions and promotion

Chapter 25 Design and Analysis of Multi-factor Test

25. 1 Introduction to experimental design

25. 1. 1 Application of experimental design

25. 1.2 Steps to solve problems in experimental design

25.2 data description

25.3 Overview of analytical methods

25.3. 1 orthogonal design method

25.3.2 Comprehensive scoring method

25.4SPSS modeling process and conclusion analysis

25.4. 1 data standardization

25.4.2 Determination of Weight of Performance Indicators

25.4.3 Using weights to find comprehensive indicators

25.4.4 Further analysis of comprehensive score

25.5 Suggestions and promotion

……