SPSS Version 14

кряка не помогает однако!!! кто знает где license файл для 14 версии стянуть?

Народ, на вкус и цвет, как и на задачу — требуются разные програмные продукты ... будте терпимей ёклмн!

Все бы хорошо, но только патч от RECOiL кривой до безобразия. Я это добро стянул еще месяц назад и на радостях поставил вместо 13.0. Забил данные и давай анализировать, а не тут то было — поле Variables пустое, как вроде ничего и не забивал. Так что, юзайте 13 версию, там хоть нормальный кряк имеется.

слушай, ratmir, пойми меня веврно.
когда вопрос стоял серьезно — поможет мне луюбимый сайт или нет, то в поиске он мне нужного ничегошеньки не наковырял. Искал по ключевым словам.
я почему такой список решил кинуть, если какому НоНаНеймевцу :) какие проблеммы нужно будет решить, он конечно везде посмотрит. И к примеру, One-Sample T Test будес светиться и на этом сайте...
...по крайней мере, это была причина такого списка. Я в свое время подарил похожему поиску тонну кислорода, милиард нервных клеток и 3 часа своей жизни. пойми, верно, не бей.
:)

Нда-ааа-аа, смогтрю я на список и балдю..., а что будет если я основные возможности SAS'а запостю ...? меня модер лишит без права восстановления. Итог: система для начинающих работать с данными, простая и (хмм-мм-м) доступная. А для настоящих пацанов только SAS. Сейчас уже 10 версия на подходе, но и возможности 8, по моему, достаточно для всего, что связано с _любыми_ даннами. Кстати, имею и могу предложить, 2 сидюка (9я уже 6 сидюков), проблемы все решены .

Statistica мне больше нраица

этот пач от RECOiL кривой
стоит подождать еще

Спасибо, serfar, за прекрасный пост. Очень своевременно, мне как раз сегодня надо обработать результаты обследования домохозяйств, а для этого SPSS — самое то.

Может для всяких гуманитариев с экономистами и бизнесменами прога подойдет, но для настоящих научных расчетов она не годится.
Меня просто трясёт от их кошмарного интерфейса и идиотской реализации, к примеру, нелинейной регрессии.
Для научной работы лучший инструмент — Origin.

программа составленна оооочень сильными людьми.
на англиском.
я сдавал c ней экзамен по advanced statistics пол года назад.
Сильнейшая прога. Умеет кучу вещей колдовать из циферек...
сегодня нет ни одного студента , который изучает бизнесс в иностранном вузе(не имею понятия о родной стране, так как учусь не в России), не знакомым с этой программой.
там и help есть неплохой с примерами. Да какими!
помню хорошо последнее, что на ней делал некрасиво и коротко выглядило так:
производство медикаментов. есть данные (около 15 величин) о группе людей от 20 до 60 лет, их доход, наличие страхового полиса и его величина, сумма, потраченная на лекарства и врачей, время, проводимое перед телевизором(по которому идет реклама того или иного препарата)сумма, потраченная на эту рекламу,и т.д. и т.п.далее цифры сортируются между потребителями женского и мужского пола, продажи как таковые этого препарата, при чем берется территория страны! и делиться в свою очередь на изучаемые участки, которые потом дают свои автономные результаты. все цифры заносят в прогу, а та тем временем выдает схемы, прогнозы, ошибки, зависимости одних величин от других, недостатки и приимущества созданных линейных уравнений.
Вам остается только понимать и "видеть" модели ВСЕГО Этого.
! с english дружить о б я з а т е л ь н о.
...я, например обновлюсь с 12ой на 14ю. Спасибо, nikiniko.
буду рад, если хотя бы еще один человек найдет в spss то, чем вся планета давным давно уже пользуется.
вот, что она умеет:
Base System
Summary Statistics Using Frequencies
Summary Statistics Using Frequencies
Using Frequencies to Study Nominal Data
Running the Analysis
Pie Chart
Frequency Table
Bar Chart
Using Frequencies to Study Ordinal Data
Running the Analysis
Frequency table
Bar chart
Using Frequencies to Study Scale Data
Running the Analysis
Statistics table
Histogram
Summarizing transformed data
Transforming the Data
Statistics table
Histogram
Summary
Related Procedures
Recommended Readings
Summary Statistics Using Descriptives
Summary Statistics Using Descriptives
Using Descriptives to Study Quantitative Data
Running the Analysis
Descriptive statistics table
Recoding the Variables
Running the Analysis
Descriptive Statistics
Finding Unusual Cases
Running the Analysis
Descriptive statistics table
Boxplots of Z Scores
Summary
Related Procedures
Recommended Readings
Exploratory Data Analysis
Exploratory Data Analysis
Descriptive Statistics across Groups
Running the Analysis
Pivoting the Descriptives Table
Using Boxplots to Compare Groups
Summary
Exploring Distributions
Running the Analysis
Numerical Descriptions of Shape
Robustness and Influential Values
Are the Distributions Normal?
Summary
Related Procedures
Recommended Readings
Analysis of Cross-classifications Using Crosstabs
Analysis of Cross-Classifications Using Crosstabs
Using Crosstabs to Study Nominal-by-Nominal Relationships
Running the Analysis
Crosstabulation Table
Chi-square Tests
Adding Contact with Employee as a Layer Variable
Crosstabulation Table
Chi-square Tests
Symmetric Measures
Directional Measures
Summary
Using Crosstabs to Study Ordinal-by-Ordinal Relationships
Running the Analysis
Crosstabulation Table
Symmetric and Directional Measures
Symmetric and Directional Measures
Summary
Using Crosstabs to Measure the Relative Risk of an Event
Running the Analysis
Crosstabulation
Risk Estimate
Odds Ratio versus Relative Risk
Adding Income Category as a Layer Variable
Rerunning the Analysis
Risk Estimate
Tests of Homogeneity of the Odds Ratio
Tests of Conditional Independence
Mantel-Haenszel Common Odds Ratio Estimate
Summary
Using Crosstabs to Measure Agreement
Running the Analysis
Kappa Measure of Agreement
Crosstabulation
Summary
Related Procedures
Recommended Readings
The Summarize Procedure
The Summarize Procedure
Using Summarize to Create Summary Reports
Creating a Grouped Summary Report
The Summary Report Table
Displaying Individual Cases
Selecting and Sorting Cases
Specifying the Analysis
Case Listing Display
Summary
Related Procedures
Recommended Readings
The Means Procedure
The Means Procedure
Using Means to Obtain Descriptive Statistics
Running the Analysis
Means Table with One Grouping Variable
Layering Variables
Re-running the Analysis
Layered Means Table
Summary
One-way ANOVA and Test of Linearity
Running the Analysis
Means of Age by Smoking Level
ANOVA and Tests of Linearity
Association Measures
Summary
Related Procedures
Recommended Readings
The OLAP Cubes Procedure
The OLAP Cubes Procedure
Analyzing Churn Using OLAP Cubes
Defining the Data
Creating an OLAP Cube
The Default OLAP Cubes Table
Drilling Down
Pivoting the Table
Pivoted OLAP Cubes Table
Summary
Related Procedures
Recommended Readings
T Tests
T Tests
One-Sample T Test
One-Sample T Test
A Production-Line Problem
Treating Each Machine as a Separate Sample
Testing Sample Means against a Known Value
Descriptive Statistics
Test Results
Related Procedures
Recommended Readings
Paired-Samples T Test
Paired-Samples T Test
Does Diet Make a Difference?
Running the Analysis
Descriptive Statistics
Pearson Correlations
Paired Test Table
Related Procedures
Recommended Readings
Independent-Samples T Test
Independent-Samples T Test
Determining the Groups in an Independent-Samples T Test
Testing Two Independent Sample Means
Running the Analysis
Group Statistics Table
Independent Samples Test Table
Pivoting the Test Table
The Pivoted Test Table
Using a Cut Point to Define the Samples
Running the Analysis
Group Statistics by Cut Point
Test Table by Cut Point
Pivoting the Test Table
Pivoted Test Table by Cut Point
Related Procedures
Recommended Readings
One-Way Analysis of Variance
One-Way Analysis of Variance
Testing the Equality of Group Variances
An Error Bar Chart
Running the Analysis
Descriptive Statistics Table
Levene Test Table
Performing a One-Way ANOVA
Running the Analysis
ANOVA Table
A Plot of Group Means
Contrasts between Means
Running the Analysis
Contrast Coefficients Table
Contrast Test Table
All Possible Comparisons between Means
Running the Analysis
Post Hoc Test Table
Robust Analysis of Variance
Before the Analysis
Running the Analysis
Levene Test Table
Standard ANOVA Table
Robust Test Table
Summary
Related Procedures
Recommended Readings
GLM Univariate
GLM Univariate
GLM Univariate Model
Using GLM Univariate to Perform a Two-Factor Analysis of Variance
Running the Analysis
Descriptive Statistics
Testing Homogeneity of the Variances
Post Hoc Tests
Estimated Marginal Means
Tests of Between-Subjects Effects
Summary
Using GLM Univariate to Perform an Analysis of Covariance
Checking Homogeneity of the Covariate Coefficients
Tests of Between-Subjects Effects
Running the Analysis
Descriptive Statistics
Testing Homogeneity of Variances
Tests of Between-Subjects Effects
Parameter Estimates
Summary
Using GLM Univariate to Account for Random Effects
Running the Analysis
Tests of Between-Subjects Effects
Adding the Random Effect
Test of Between-Subjects Effects
Summary
Related Procedures
Recommended Readings
Bivariate Correlations
Bivariate Correlations
Using Correlations to Study the Association between Motor Vehicles Sales and Fuel Efficiency
Running the Analysis
Correlation Matrix
Improving Correlation Estimates
Correlations
Improving Correlation Estimates: Splitting the File
Correlations
Nonparametric Correlation Estimates
Correlations
Summary
Related Procedures
Recommended Readings
Partial Correlations
Partial Correlations
Using Partial Correlations to Unravel "Relationships"
Running the Analysis
Partial Correlations Table
Related Procedures
Linear Regression
Linear Regression
The Linear Regression Model
Using Linear Regression to Predict Polishing Times
Creating a Scatterplot of the Dependent by the Independent
Running the Analysis
Coefficients
Checking the Model Fit
Checking the Normality of the Error Term
Checking Independence of the Error Term
Identifying Influential Points
Summary
Using Linear Regression to Model Vehicle Sales
Running the Analysis
Checking the Model Fit
Coefficients
Collinearity Diagnostics
Running a Stepwise Linear Regression
Collinearity Diagnostics
Checking the Model Fit
Stepwise Coefficients
Checking the Normality of the Error Term
Casewise Diagnostics
Residual Scatterplots
Identifying Influential Points
Summary
Related Procedures
Recommended Readings
Discriminant Analysis
Discriminant Analysis
Discriminant Analysis Model
Using Discriminant Analysis to Assess Credit Risk
Preparing the Data for Analysis
Running the Analysis
Classifying Customers as High or Low Credit Risks
Checking Collinearity of Predictors
Checking for Correlation of Group Means and Variances
Checking Homogeneity of Covariance Matrices
Assessing the Contribution of Individual Predictors
Tests of Equality of Group Means
Standardized Canonical Discriminant Function Coefficients
Structure Matrix
Assessing Model Fit
Eigenvalues
Wilks' Lambda
Model Validation
Specifying Separate-Groups Covariance Matrices
Adjusting Prior Probabilities
Summary
Using Discriminant Analysis to Classify Segment Telecommunications Customers
Running the Analysis
Stepwise Discriminant Analysis
A Note of Caution Concerning Stepwise Methods
Checking Model Fit
Structure Matrix
Territorial Map
Classification Results
Summary
Related Procedures
Recommended Readings
Factor Analysis
Factor Analysis
Factor Analysis Methods
Using Factor Analysis for Data Reduction
Running the Analysis
Communalities
Total Variance Explained
Scree Plot
Rotated Component Matrix
Component Score Coefficient Matrix
Scatterplot Matrix of Component Scores
Summary
Using Factor Analysis for Structure Detection
Running the Analysis
KMO and Bartlett's Test
Communalities
Total Variance Explained
Scree Plot
Factor Matrix
Rotated Factor Matrix
Summary
Related Procedures
Recommended Readings
TwoStep Cluster Analysis
TwoStep Cluster Analysis
Clustering Principles
Using TwoStep Cluster Analysis to Classify Motor Vehicles
Running the Analysis
Auto-Clustering
Cluster Distribution
Cluster Profiles
Attribute Importance
Summary
Related Procedures
Hierarchical Cluster Analysis
Hierarchical Cluster Analysis
Clustering Principles
Using HCA to Classify Automobiles
Preparing the Data
Running the Analysis
Dendrogram
Agglomeration Schedule
Complete Linkage Solution
Agglomeration Schedule
Dendrogram
Summary
Using HCA to Study Relationships between Telecommunications Services
Running the Analysis
Agglomeration Schedule
Dendrogram
Solution Using the Jaccard Measure
Dendrogram
Summary
Related Procedures
Recommended Readings
K-Means Cluster Analysis
K-Means Cluster Analysis
Clustering Principles
Using K-Means to Classify Customers
Running the Analysis
Initial Cluster Centers
Iteration History
ANOVA
Final Cluster Centers
Distances between Final Cluster Centers
Number of Cases in Each Cluster
Building a Four-Cluster Solution
Plot of Distances from Cluster Center by Cluster Membership
Final Cluster Centers
Distances between Final Cluster Centers
Number of Cases in Each Cluster
Summary
Related Procedures
Recommended Readings
Nonparametric Tests
Nonparametric Tests
The Chi-Square Test
The Chi-Square Test
Testing Independence
Preparing the Data
Running the Analysis
Chi-Square Frequency Table
Chi-Square Test Table
Testing a Specific Range
Rerunning the Analysis
Frequency Table of Weekday Data
Chi-Square Test of Weekday Data
Summary
Customizing Expected Values
Preparing the Data
Running the Analysis
Assessing the Fit between Observed and Expected Responses
Summary
Related Procedures
Recommended Readings
The Binomial Test Procedure
The Binomial Test Procedure
Comparing Several Distributions
Preparing the Data
Running the Analysis
Descriptive Statistics Table
The Binomial Test Table
Summary
Using a Cut Point to Define the Samples
Preparing the Data
Running the Analysis
Income Quartiles by Churn Group
Binomial Test Table by Churn Group
Summary
Related Procedures
Recommended Readings
The Runs Test Procedure
The Runs Test Procedure
Examining Usability Test Results
Determining a Cut Point
Bar Chart of the Test Variable
Testing Multiple Cut Points
Descriptive Statistics Table
Runs Test Table with a Median Cut Point
Runs Test Table with a Modal Cut Point
Runs Test Table with a Custom Cut Point
Summary
Related Procedures
Recommended Readings
One-Sample Kolmogorov-Smirnov Procedure
One-Sample Kolmogorov-Smirnov Procedure
Assessing Goodness of Fit
Running the Analysis
One-Sample Kolmogorov-Smirnov Test Table
Goodness of Fit within Groups
Splitting the File
Running the Analysis
Descriptive Statistics by Group
Test Tables by Group
Summary
Related Procedures
Recommended Readings
Nonparametric Tests for Two Independent Samples
Nonparametric Tests for Two Independent Samples
Methods for Two Independent Samples
Using the Mann-Whitney Test to Test Ordinal Outcomes
Running the Analysis
Rank Table
Mann-Whitney and Wilcoxon Tests Table
Using the Two-Sample Kolmogorov-Smirnov Test to Compare Distributions
Preparing the Data
Running the Analysis
Two-Sample K-S Frequency Table
Two-Sample K-S Test Table
Related Procedures
Recommended Readings
Nonparametric Tests for Multiple Independent Samples
Nonparametric Tests for Multiple Independent Samples
Methods for Multiple Independent Samples
Using the Median Test to Detect Group Differences
Obtaining the Analysis
Median Test Statistics Table
Median Test Frequency Table
Median Test Table
Using Kruskal-Wallis to Test Ordinal Outcomes
Running the Analysis
Kruskal-Wallis Rank Table
Kruskal-Wallis Test Table
Related Procedures
Recommended Readings
Nonparametric Tests for Two Related Samples
Nonparametric Tests for Two Related Samples
Testing a Sample Median Against a Known Value
Running the Analysis
Wilcoxon Signed-Ranks Rank Table
Wilcoxon Signed-Ranks Test Table
Using the McNemar Test in a Pre-Post Design
Defining the McNemar Analysis
McNemar Test Crosstabulation Table
McNemar Test Chi-Square Table
Related Procedures
Recommended Readings
Nonparametric Tests for Multiple Related Samples
Nonparametric Tests for Multiple Related Samples
Testing the Usability of a Web Site
Running the Analysis
Descriptive Statistics Table
Cochran Frequency Table
Cochran Test Table
Using the Friedman Test on Related Ordinal Measures
Defining the Friedman Analysis
Friedman Rank Table
Friedman Test Table
Related Procedures
Recommended Readings
Ratio Statistics
Ratio Statistics
Using Ratio Statistics to Aid Property Value Assessment
Running the Analysis
Ratio Statistics
Summary
Related Procedures
Recommended Readings
ROC Curve
ROC Curve
Using ROC Curve to Evaluate Assay Performance
Running the Analysis
ROC Curve
Area under the Curve
Coordinates of the Curve
Summary
Using ROC Curves to Choose between Competing Classification Schemes
Running the Analysis
ROC Curve
Area under the Curve
Summary
Related Procedures
Recommended Readings
Measures of Reliability in Scale Problems
Reliability Analysis
Using Reliability Measures to Analyze Survey Items
Running the Analysis
Descriptive Statistics
Cronbach's Alpha
Split-Half Coefficients
Guttman's Lower Bounds
Parallel and Strictly Parallel
Using Reliability Measures to Analyze Inter-Rater Agreement
Running the Analysis
Descriptive Statistics
Intraclass Correlation Coefficients
Summary
Recommended Readings
Control Charts
Control Charts
Control Chart Principles
Using X-bar and R Charts to Monitor Shampoo pH
Running the Analysis
Range Chart
Relationship between the R Chart and X-bar Chart
X-bar Chart
Process Statistics
Summary
Using p Charts to Track the Proportion of Defective Units
Running the Analysis
p Chart
Recommended Readings
Advanced Models Option
Multivariate General Linear Modeling
Multivariate General Linear Modeling
GLM Multivariate
GLM Multivariate
The Model
Multivariate Analysis of Variance (MANOVA) Using the GLM Multivariate Procedure
Running the Analysis
SSCP Matrices and Multivariate Tests
Contrast Results
Testing Homogeneity of Covariance Matrices
Using Log-transformed Treatment Costs
Testing Homogeneity of Covariance Matrices
Is the Assumption of Homogeneity Violated?
Contrast Results
Summary
Using GLM Multivariate to Profile Churners
Running the Analysis
Multivariate tests
Profile Plots
Summary
Related Procedures
Recommended Readings
GLM Repeated Measures
GLM Repeated Measures
The GLM Repeated Measures Model
A Repeated Measures Analysis of Variance
Preparing the Data File
Running the Analysis
Between-Subjects Effects
Profile Plots
Within-Subjects SSCP Matrices
Multivariate Tests of Within-Subjects Effects
Testing Homogeneity of Covariance Matrices
Mauchly's Test of Sphericity
Univariate Tests of Within-Subjects Effects
Contrast Results
Summary
A Doubly Multivariate Analysis of Variance
Running the Analysis
Multivariate Tests
Contrast Results
Estimated Marginal Means
Profile Plots
Summary
Related Procedures
Recommended Readings
Variance Components
Variance Components
The Model
Estimation Methods
ANOVA Method
MINQUE Method
Maximum Likelihood Method
Restricted Maximum Likelihood Method
Using Variance Components to Assess a Random Effect
Running the Analysis
Variance Estimates
Computing Variance Estimates (ANOVA Method)
Restricted Maximum Likelihood Estimation
Iteration History
Variance Estimates
Asymptotic Covariance Matrix
MINQUE (1) Estimation
Variance Estimates
MINQUE (0) Estimation
Variance Estimates
Summary
Related Procedures
Recommended Readings
Linear Mixed Models
Linear Mixed Models
The Linear Mixed Model
Using Linear Mixed Models to Analyze Product Test Results From Multiple Markets
Running the Analysis
Model Dimension
Fixed Effects
Covariance Parameters
Random Effect Covariance (G) Matrix
Summary
Using Linear Mixed Models to Analyze Repeated Measurements
Preparing the Data File
Running the Analysis
Fixed Effects
Treating Time as a Repeated Effect
Running the Analysis
Model Dimension
Information Criteria
Fixed Effects
Covariance Parameters
Residual Covariance (R) Matrix
Restricting the Covariance Structure
Running the Analysis
Model Dimension
Residual Covariance (R) Matrix
Information Criteria
A Likelihood Ratio Test
Computing the Likelihood Ratio Statistic
Computing the Significance Value of the Test Statistic
Summary
Using Linear Mixed Models to Analyze a Crossover Trial
Running the Analysis
Model Dimension
Fixed Effects
Covariance Parameters
Using Repeated Effects to Model the Crossover Trial
Running the Analysis
Warning
Model Dimension
Information Criteria
Fixed Effects
Covariance Parameters
Residual Covariance (R) Matrix
Specifying an Unstructured Covariance Matrix for the Repeated Effects
Running the Analysis
Model Dimension
Information Criteria
Fixed Effects
Covariance Parameters
Residual Covariance (R) Matrix
Specifying the Treatment as the Repeated Effect
Running the Analysis
Model Dimension
Information Criteria
Fixed Effects
Residual Covariance (R) Matrix
Summary
Using Linear Mixed Models to Model Random Effects and Repeated Measures
Running the Analysis
Model Dimension
Fixed Effects
Covariance Parameters
An Unstructed Covariance Matrix for Repeated Effects
Running the Analysis
Model Dimension
Information Criteria
Fixed Effects
Random Effect Covariance (G) Matrix
Residual Covariance (R) Matrix
Summary
Related Procedures
Recommended Readings
Loglinear Modeling
Loglinear Modeling
General Loglinear Analysis
General Loglinear Analysis
The General Loglinear Model
Using General Loglinear Analysis to Model Response to Mailings
Running the Analysis
Goodness-of-Fit Tests
Cell Count and Residuals
Adding the Interaction to the Model
Running the Analysis
Parameter Estimates
Summary
Using General Loglinear Analysis to Model Accident Rates
Weighting the Cases
Running the Analysis
Parameter Estimates
Summary
Paired Data
Models for Paired Data
Weighting the Cases
Running the Symmetry Model
Goodness-of-fit Tests
Running the Quasi-Symmetry Model
Goodness-of-fit Tests
Testing Marginal Homogeneity
Computing the Statistic
Running the Quasi-Independence Model
Goodness-of-fit Tests
Summary
Related Procedures
Recommended Readings
Logit Loglinear Analysis
Logit Loglinear Analysis
The Model
Using Logit Loglinear Analysis to Model Consumer Preference of Packaged Goods
Running the Analysis
Goodness-of-Fit
Cell Count and Residuals
Analysis of Dispersion
Logit Loglinear Analysis Parameter Estimates
Summary
Related Procedures
Recommended Readings
Ordinal Regression
Ordinal Regression (PLUM)
The Ordinal Regression Model
Using Ordinal Regression to Build a Credit Scoring Model
Constructing a Model
Identifying the Outcome Variable
Choosing Predictors for the Location Model
Scale Component
Choosing a Link Function
Running the Analysis
Evaluating the Model
Predictive Value of the Model
Chi-Square-Based Fit Statistics
Pseudo R-Squared Measures
Classification Table
Test of Parallel Lines
Evaluating the Choice of Link Function
Revising the Model
Model-fitting information
Pseudo R-squared Measures
Classification Table
Interpreting the Model
Summary : Using the Model to Make Predictions
Related Procedures
Recommended Readings
Cox Regression
Cox Regression
The Cox Regression Model
The Proportional Hazards Model
Stratified Proportional Hazards
Time-Dependent Covariates
Using Cox Regression to Model Customer Time to Churn
Running the Analysis
Censored Cases
Categorical Variable Codings
Variable Selection
Covariate Means and Patterns
Survival Curve
Hazard Curves
Summary
Cox Regression with a Time-Dependent Covariate
Running the Analysis
Creating the Diagnostic Scatterplot
Adding the Time-Dependent Covariate
Variables in the Equation
Summary
Recommended Readings
Regression Models Option
Binary Logistic Regression
Binary Logistic Regression
The Logistic Regression Model
Using Binary Logistic Regression to Assess Credit Risk
Preparing the Data for Analysis
Running the Analysis
Model Diagnostics
Tests of Model Fit
Change in Deviance Versus Predicted Probabilities
Cook's Distances Versus Predicted Probabilities
Choosing the Right Model
Variable Selection
R-Squared Statistics
Classification
Logistic Regression Coefficients
Summary
Related Procedures
Recommended Readings
Multinomial Logistic Regression
Multinomial Logistic Regression
The Multinomial Logistic Regression Model
Using Multinomial Logistic Regression to Profile Consumers of Packaged Goods
Running the Analysis
Model Diagnostics
Warnings
Goodness-of-Fit
Observed and Predicted Frequencies
Model Fitting Information
Choosing the Right Model
Likelihood Ratio Tests
Pseudo R Square
Classification Table
Multinomial Logistic Regression Coefficients
Summary
Using Multinomial Logistic Regression to Classify Telecommunications Customers
Running the Analysis
Stepwise Multinomial Logistic Regression
A Note of Caution Concerning Stepwise Methods
Classification Results
Summary
Using Multinomial Logistic Regression to Analyze a 1-1 Matched Case-Control Study
Data File Setup for Case-Control
Running the Analysis
Model Diagnostics
Model Fitting Information
Choosing the Right Model
Likelihood Ratio Tests
Multinomial Logistic Regression Coefficients
Summary
Related Procedures
Recommended Readings
Complex Samples Option
Planning for Complex Samples
Planning for Complex Samples
Complex Samples Sampling Wizard
Complex Samples Sampling Wizard
Obtaining a Sample from a Full Sampling Frame
Using the Wizard
Plan Summary
Sampling Summary
Sample Results
Obtaining a Sample from a Partial Sampling Frame
Using the Wizard to Sample from the First Partial Frame
Sample Results
Using the Wizard to Sample from the Second Partial Frame
Sample Results
Related Procedures
Recommended Readings
Complex Samples Analysis Preparation Wizard
Complex Samples Analysis Preparation Wizard
Using the Complex Samples Analysis Preparation Wizard to Ready NHIS Public Data
Using the Wizard
Summary
Related Procedures
Recommended Readings
Complex Samples Analysis Procedures: Tabulation
Complex Samples Analysis Procedures: Tabulation
Complex Samples Frequencies
Complex Samples Frequencies
Frequencies Analysis of Nutritional Supplements Usage
Running the Analysis
Frequency Table
Frequency by Subpopulation
Summary
Related Procedures
Recommended Readings
Complex Samples Crosstabs
Complex Samples Crosstabs
Using Crosstabs to Measure the Relative Risk of an Event
Running the Analysis
Crosstabulation
Risk Estimate
Odds Ratio versus Relative Risk
Risk Estimate by Subpopulation
Summary
Related Procedures
Recommended Readings
Complex Samples Analysis Procedures: Descriptives
Complex Samples Analysis Procedures: Descriptives
Complex Samples Descriptives
Complex Samples Descriptives
Using Complex Samples Descriptives to Analyze Activity Levels
Running the Analysis
Univariate Statistics
Univariate Statistics by Subpopulation
Summary
Related Procedures
Recommended Readings
Complex Samples Ratios
Complex Samples Ratios
Using Complex Samples Ratios to Aid Property Value Assessment
Running the Analysis
Ratios
Pivoting the Ratios Table
Pivoted Ratios Table
Summary
Related Procedures
Recommended Readings
Data Files Used
Data Files Used Table of ContentsSelect a topic above.