area of spss application in manufacturing

8/13/2019 Area of SPSS Application in Manufacturing

1/21

IBM SPSS Statistics version 22.0.00


2/21

Introduction

IBM SPSS Statistics is an integrated family of products that addresses the entire analytical process, fro

planning to data collection to analysis, reporting and deployment. With more than a dozen fully integrate

modules to choose from, you can find the specialized capabilities you need to increase revenue, outperfor

competitors, conduct research and make better decisions.

In todays data driven landscape, the ability to analyze information to drive decision making and solve problem

is fundamental for Success. IBM SPSS Statistics has help organization of all types:

- Identify which customers are likely to respond to specific promotional offers.

- Boost profits and reduce costs by targeting only the most valuable customers.

- Forecast future trends to better plan organizational strategies, logistics, and manufacturing process.

- Detect fraud and minimize business risk.

- Analyze either / or outcomes, such as patient survival rates or good / bad credit risks.- Report results clearly and efficiently.

- Understand which characteristics consumers relate most closely to your brand.

- Identify groups, discover relationships between groups and predict future events.

IBM SPSS Statistics offers the full scope of Statistical and Analytical capabilities that organizations requir

Its an easy to use comprehensive software solution that:

- Addresses the entire analytical process from planning and data preparation to analysis, reporting an

deployment.

- Provides tailored functionality and custom interfaces for different skill levels and function

responsibilities of business users, analyst and Statisticians.

- Includes flexible deployment options from stand-alone desktop to enterprise-strength server versions.

- Provides faster performance and more accurate results, compared to non-statistical, spreadsheet-typ

software.

- Works with all common data types, external programming languages, operating systems and file types.

- Offers a broad range of specialized techniques to spend productivity and increase effectiveness.


3/21

IBM SPSS Statistics Modules How are used?

IBM SPSS Statistics is an integrated family of products that offers a rich set of capabilities for every stage o

the analytical process. Choose from a broad range of tools, tests and techniques so you can quickly an

confidently perform any type of analysis.

IBM SPSS Statistics Baseforms the foundation for many types of statistical analyses, allowing a quick look

data and its easy preparation for analysis. Easily build charts with sophisticated reporting capabilities, formula

hypotheses for additional testing, clarify relationships between variables, create clusters, identify trends an

make predictions.

IBM SPSS Advanced Statisticsmakes analysis and conclusions more accurate when working with compl

relationships in data, it offers powerful and sophisticated univariate and multivariate analysis techniques.

IBM SPSS Bootstrappingmakes testing the stability and reliability of your models easy.

IBM SPSS Categoriesprovides tools to obtain clear insight into complex categorical, numerical and hig

dimensional data. Understand which characteristics consumers relate most closely to your brand, or determin

customer perception of your products compared to others.

IBM SPSS Complex Samplesincorporates complex sample designs into data analysis, with specialize

planning tools and statistics, reducing the risk of reaching incorrect or misleading inferences for stratifie

clustered or multistage sampling. This module is indispensable for survey and market researchers, pub

opinion researchers or social scientists seeking to reach more accurate conclusions when working with samp

survey methodology.

IBM SPSS Conjointhelps market researchers develop successful products, giving a realistic way to measu

how individual attributes affect peoples preferences. When used with competitive product market research f

your new products, you are less likely to overlook product dimensions that are important to your customers

constituents, and more likely to successfully meet their needs.
http://www.ibm.com/software/products/in/en/spss-stats-basehttp://www.ibm.com/software/products/in/en/spss-stats-basehttp://www.ibm.com/software/products/in/en/spss-advanced-statshttp://www.ibm.com/software/products/in/en/spss-advanced-statshttp://www.ibm.com/software/products/in/en/spss-bootstrappinghttp://www.ibm.com/software/products/in/en/spss-bootstrappinghttp://www.ibm.com/software/products/in/en/spss-categorieshttp://www.ibm.com/software/products/in/en/spss-categorieshttp://www.ibm.com/software/products/in/en/spss-complex-sampleshttp://www.ibm.com/software/products/in/en/spss-complex-sampleshttp://www.ibm.com/software/products/in/en/spss-conjointhttp://www.ibm.com/software/products/in/en/spss-conjointhttp://www.ibm.com/software/products/in/en/spss-conjointhttp://www.ibm.com/software/products/in/en/spss-complex-sampleshttp://www.ibm.com/software/products/in/en/spss-categorieshttp://www.ibm.com/software/products/in/en/spss-bootstrappinghttp://www.ibm.com/software/products/in/en/spss-advanced-statshttp://www.ibm.com/software/products/in/en/spss-stats-base


4/21

IBM SPSS Custom Tablescombines comprehensive analytical capabilities with interactive table-buildi

features to help you easily understand your data and quickly summarize your results in appropriate styles f

different audiences. Use IBM SPSS Custom Tables to present survey, customer satisfaction, polling an

compliance reporting results.

IBM SPSS Data Preparationgives analysts advanced techniques to streamline the data preparation stage

the analytical process, prior to analysis. While basic data preparation tools are included in IBM SPSS Statisti

Base, IBM SPSS Data Preparation provides specialized techniques to prepare your data for more accura

analyzes and results.

IBM SPSS Decision Treeshelps you better identify groups, discover relationships between them and predi

future events through the exploration of results and visual determination of how your model flows. Crea

visual classification and decision trees directly within the Statistics suite of products and present results in a

intuitive manner.

IBM SPSS Direct Marketinghelps marketers perform various kinds of analyses easily, without requiring

detailed understanding of statistics. Understand your customers in greater depth, improve your marketi

campaigns and maximize the ROI of your marketing budget.

IBM SPSS Exact Testsenables you to use small samples and still feel confident about the results. With th

money saved using smaller sample sizes, you can conduct surveys or test direct marketing programs more ofte

More than 30 exact tests, which cover the entire spectrum of nonparametric and categorical data problems f

small or large datasets, are included.

IBM SPSS Forecastingenables analysts to predict trends and develop forecasts quickly and easily witho

being an expert statistician. IBM SPSS Forecasting has the advanced statistical techniques needed to work wi

time-series data regardless of your level of expertise.

IBM SPSS Missing Valuesfinds relationships between any missing values in your data and other variable

Missing data can seriously affect your modelsand your results. Used by survey researchers, social scientist

data miners and market researchers to validate data.
http://www.ibm.com/software/products/in/en/spss-custom-tableshttp://www.ibm.com/software/products/in/en/spss-custom-tableshttp://www.ibm.com/software/products/in/en/spss-data-preparationhttp://www.ibm.com/software/products/in/en/spss-data-preparationhttp://www.ibm.com/software/products/in/en/spss-decision-treeshttp://www.ibm.com/software/products/in/en/spss-decision-treeshttp://www.ibm.com/software/products/in/en/spss-direct-marketinghttp://www.ibm.com/software/products/in/en/spss-direct-marketinghttp://www.ibm.com/software/products/in/en/spss-exact-testshttp://www.ibm.com/software/products/in/en/spss-exact-testshttp://www.ibm.com/software/products/in/en/spss-forecastinghttp://www.ibm.com/software/products/in/en/spss-forecastinghttp://www.ibm.com/software/products/in/en/spss-missing-valueshttp://www.ibm.com/software/products/in/en/spss-missing-valueshttp://www.ibm.com/software/products/in/en/spss-missing-valueshttp://www.ibm.com/software/products/in/en/spss-forecastinghttp://www.ibm.com/software/products/in/en/spss-exact-testshttp://www.ibm.com/software/products/in/en/spss-direct-marketinghttp://www.ibm.com/software/products/in/en/spss-decision-treeshttp://www.ibm.com/software/products/in/en/spss-data-preparationhttp://www.ibm.com/software/products/in/en/spss-custom-tables


5/21

IBM SPSS Neural Networksoffers non-linear data modeling procedures that enable you to discover mo

complex relationships in your data. Choose from algorithms that can be used for classification (categoric

outcomes) and prediction (numerical outcomes) to develop more accurate and effective predictive models th

provide deeper insight and better decision-making.

IBM SPSS Regressionenables you to predict categorical outcomes and apply a wide range of nonline

regression procedures. Effective where ordinary regression techniques are limiting or inappropriate: F

example, studying consumer buying habits or responses to treatments, measuring academic achievement, an

analyzing credit risks.
http://www.ibm.com/software/products/in/en/spss-neural-networkshttp://www.ibm.com/software/products/in/en/spss-neural-networkshttp://www.ibm.com/software/products/in/en/spss-regressionhttp://www.ibm.com/software/products/in/en/spss-regressionhttp://www.ibm.com/software/products/in/en/spss-regressionhttp://www.ibm.com/software/products/in/en/spss-neural-networks


6/21

IBM SPSS Statistics Modules Description

IBM SPSS Advanced Statistics:

More Accurately Analyze Complex Relationships Using Powerful Univariate and Multivariate Analysis

Make your analysis more accurate and reach more dependable conclusions with procedures designed to fit th

inherent characteristics of data describing complex relationships. SPSS Advanced Statistics (formerly calleAdvanced Models), provides a powerful set of sophisticated univariate and multivariate analysis techniques f

real-world problems, such as:

Medical research:Analyze patient survival rates

Manufacturing:Assess production processes

Pharmaceutical:Report test results to the FDA

Market research:Determine product interest levels

Access a Range of Powerful Models

In addition to the general linear models (GLM) and mixed models procedures, SPSS Advanced Models now offethe generalized linear models (GENLIN) and generalized estimating equations (GEE) procedures.

GENLIN include widely used statistical models, such as linear regression for normally distribute

responses, logistic models for binary data, and loglinear models for count data. This procedure als

offers many useful statistical models through its very general model formulation.

GEE extend generalized linear models to accommodate correlated longitudinal data and clustered data

SPSS Advanced Statistics continues to offer the following procedures:

General linear models (GLM) procedure:Provides you with more flexibility to describe the relationshbetween a dependent variable and a set of independent variables

Linear mixed models, also known as hierarchical linear models (HLM) procedure: Expands the gene

linear models used in the GLM procedure so that you can analyze data that exhibit correlation and no

constant variability. Create more accurate models when working with nested-structure data, and mod

the mean, variance, and covariance in your data


7/21

SPSS Categories:

Predict outcomes and reveal relationships in categorical data

Unleash the full potential of your data through predictive analysis, statistical learning, perceptual mappin

preference scaling, and dimension reduction techniquesincluding optimal scaling of your variables. SP

Categories provides you with all the tools you need to obtain clear insight into complex categorical and numer

data, as well as high-dimensional data. For example, use SPSS Categories to understand which characteristi

consumers relate most closely to your brand, or to determine customer perception of your products comparto other products you or your competitors offer.

You can visually interpret datasets and see how rows and columns relate in large tables of scores, count

ratings, rankings, or similarities. This gives you the ability to:

Work with and understand nominal and ordinal data with procedures similar to conventional regressio

principal components, and canonical correlation

Deal with non-normal residuals in numeric data or nonlinear relationships between predictor variabl

and the outcome variable. You can now use Ridge Regression, the Lasso, the Elastic Net, variab

selection, and model selection for both numeric and categorical data.

Turn qualitative variables into quantitative ones

The advanced procedures available in SPSS Categories enable you to perform additional statistical operations

categorical data.

Use SPSS Categories' optimal scaling procedures to assign units of measurement and zero-points to yo

categorical data

Choose from state-of-the art procedures for model selection and regularization

Perform correspondence and multiple correspondence analyses to numerically evaluate similariti

between two or more nominal variables in your dataset Summarize your data according to important components by using principal components analysis

Quantify your ordinal and nominal variables with an optimal scaling correlation matrix

Use nonlinear canonical correlation analysis to incorporate and analyze variables of differe

measurement levels

Graphically display underlying relationships

SPSS Categories' dimension reduction techniques enable you to clarify relationships in your data by usin

perceptual maps and biplots.

Perceptual maps are high-resolution summary charts that graphically display similar variables

categories close to each other. They provide you with unique insight into relationships between mo

than two categorical variables.

Biplots and triplots enable you to look at the relationships among cases, variables, and categories. F

example, you can define relationships between products, customers, and demographic characteristics.


8/21

By using the preference scaling feature, you can further visualize relationships among objects. The breakthrou

algorithm on which this procedure is based enables you to perform non-metric analyses for ordinal data an

obtain meaningful results. The proximities scaling procedure allows you to analyze similarities between object

and incorporate characteristics for objects in the same analysis.

SPSS Complex Samples:

Correctly and Easily Compute Statistics for Complex Sampling

Do you analyze data from survey or market research, public health datasets, or government agencies? Do yo

use sample survey methodology in your research, or are your data likely to come from a public-use dataset th

includes complex sample designs? Are you confident that the statistical methods you use to analyze samp

survey data provide you with the most accurate results?

If you're working with complex sample designs, such as stratified, clustered or multistage sampling, you nee

specialized statistical techniques to account for the sample design and its associated standard errors.

SPSS Complex Samples, an add-on module for IBM SPSS Statistics, provides the specialized planning tools an

statistics you need when working with sample survey data. It enables you to make more statistically va

inferences for a population by incorporating the sample design into survey analysis. You can more accurate

work with numerical and categorical outcomes in complex sample designs using two algorithms for analysis an

prediction. In addition, a new algorithm enables you to predict time to an event. This add-on module is

indispensable statistical tool for survey and market researchers, public opinion researchers, or social scientis

and enables you to reach more accurate conclusions when working with sample survey methodology.

Work efficiently and easily

Only SPSS Complex Samples makes understanding and working with your complex sample survey results easThrough the intuitive interface, you can analyze data and interpret results. When you're finished, you ca

publish public-use datasets and include your sampling and analysis plans. These plans act as a template an

allow you to save all the decisions made when creating the plandefine it once and you're done. This sav

time and improves accuracy for yourself and others who may want to plug your plans into the data to replica

results or pick up where you left off.

To begin your work in SPSS Complex Samples, use the wizards, which prompt you for the many factors you mu

consider before you start planning. If you are creating your own samples, use the Sampling Wizard to define th

scheme and draw the sample. If you're using public-use datasets that already have samples, such as tho

provided by the Centers for Disease Control and Prevention (CDC), use the Analysis Plan Wizard to specify hothe samples were defined and how standard errors should be estimated. Once you create a sample or spec

standard errors, you can create plans, analyze your data, and produce results (see diagram below for workflow


9/21

Accurate analysis of survey data is easy in SPSS Complex Samples. Start with one of the wizards (which on

depends on your data source) and then use the interactive interface to create plans, analyze data an

interpret results.

You can use the following types of sample design information with SPSS Complex Samples:

Stratified samplingIncrease the precision of your sample or ensure a representative sample from key grou

by choosing to sample within subgroups of the survey population. For example, subgroups might be a speci

number of males or females or contain people in certain job categories, people of a certain age group and so o

Clustered samplingselect clusters, which are groups of sampling units, for your survey. Clusters can includ

schools, hospitals or geographic areas with sampling units that might be students, patients or citizens. Clusteri

often helps makes surveys more cost-effective.

Multistage samplingSelect an initial or first-stage sample based on groups of elements in your populatiothen create a second-stage sample by drawing a sub-sample from each selected unit in the first-stage sampl

By repeating this option, you can select a higher-stage sample. For example, in a face-to-face survey, you mig

sample individuals within households and city blocks.


10/21

SPSS Conjoint:

Easily Discover What People Value

SPSS Conjoint gives you a realistic way to measure how individual product attributes affect consumer and citize

preferences. With SPSS Conjoint, you can easily measure the tradeoff effect of each product attribute in t

context of a set of product attributesas consumers do when making purchasing decisions.

When you use both conjoint analysis and competitive product market research for your new products, you'll bless likely to overlook product dimensions that are important to your customers and more likely to develo

products and services that sell.

Answer your critical product market research questions:

What product attributes do my customers care about?

What are the most preferred attribute levels?

How can I most effectively perform pricing and brand equity studies?

You can answer all of your questions by analyzing your new products before you spend valuable resources tryi

to bring successful products or services to market. Use SPSS Conjoint to focus your efforts on the service

product development that has the best chance of succeeding.

SPSS Conjoint has the procedures you need to conduct service and product development planning:

Orthoplan

Plancards

Conjoint


11/21

SPSS Custom Tables:

Easily Analyze and Communicate Your Results

SPSS Custom Tables (formerly called SPSS Tables), enables you to better understand your data, and easily repo

your results to those who need them.

More than a simple reporting program, SPSS Custom Tables providescomprehensive analysis capabilitiesth

help you learn from your data. For example, you can:

Compare means or proportions for demographic groups, customer segments, time periods, or oth

categorical variables, when you include inferential statistics

Select summary statisticsfrom simple counts for categorical variables to measures of dispersiona

sort categories by any summary statistic used

Choose from three significance tests:Chi-square test of independence, comparison of column mea

( ttest), or comparison of column proportions ( ztest)

When it's time to create your tables, use the interactive table preview builder to see how they look as y

build them. When you're finished, produce all results as SPSS pivot tables. SPSS Tables provides many timsaving capabilities for building custom tables quickly. For example, you can:

Create a tableby simply dragging your variables onto the table preview builder

Preview tables as you build them,so you can make any necessary changes along the way

Use category management featuresto exclude specific categories, display missing value cells, ad

subtotals to your table, and more

Automate reportsthat you need more often

Export tables to Microsoft Word or Excelfor use in reports
http://www.spss.com/tables/analysis.htmhttp://www.spss.com/tables/analysis.htmhttp://www.spss.com/tables/analysis.htmhttp://www.spss.com/tables/analysis.htm


12/21

SPSS Data Preparation:

Improve Data Preparation for More Accurate Results

All researchers have to prepare their data prior to analysis. While data preparation tools are included

the SPSS Baseproduct, sometimes you need more specialized techniques to get your data ready. With the SPS

Data Preparation add-on module, you gain new techniques to help you streamline the data preparation stage

the analytical process. This module helps you to:

Identify suspicious or invalid cases, variables, and data values

View patterns of missing data

Summarize variable distributions

More accurately get your data ready for analysis


13/21

SPSS Decision Trees:

Easily Identify Groups and Predict Outcomes

The SPSS Decision Trees add-on module (formerly called SPSS Classification Trees) creates classification an

decision trees directly within IBM SPSS Statistics Base to help you better identify groups, discover relationshi

between groups, and predict future events.

This add-on module features highly visual classification and decision trees. These trees enable you to presecategorical results in an intuitive manner, so you can more clearly explain categorical results to non-technic

audiences. SPSS Decision Trees enables you to explore results and visually determine how your model flow

This helps you find specific subgroups and relationships that you might not uncover using more tradition

statistics. SPSS Decision Trees includes four established tree-growing algorithms.

Use SPSS Decision Trees in a variety of applications in which you need to identify groups. These application

include:

Database marketing

Market research Credit risk scoring

Program targeting

Marketing in the public sector

SPSS Exact Tests:

More Accurately Analyze Small Datasets or Those with Rare Occurrences


14/21

Analyze your data more completely using SPSS Exact Tests. This add-on module for SPSS gives you what

needed to more accurately work with small samples and analyze rare occurrences in large databases.

Use small samples credibly

When a large sample size is impossible or costly, SPSS Exact Tests enables you to use small samples and still fe

confident about the results. With the money saved using smaller sample sizes, you can conduct surveys or te

direct marketing programs more often. Stay ahead of the competition by using these resources to find ne

opportunities.

Easily interpret and apply exact tests

SPSS Exact Tests are easy to run. You can calculate them anytime with just a click of a buttonduring yo

original analysis or when you rerun it. With SPSS Exact Tests, there is no steep learning curve, because you don

need to learn any new statistical theories or procedures. You simply interpret the exact tests results the sam

way you already interpret the results in SPSS Base.

You'll always have the right statistical test for your data situation. SPSS Exact Tests provides you with more tha

30 exact tests, which cover the entire spectrum of nonparametric and categorical data problems for small

large datasets. These tests include one-sample, two-sample and K-sample tests on independent or relate

samples, goodness-of-fit tests, tests of independence in RxC contingency tables and on measures of associatio

SPSS Forecasting:

Build Expert Time-Series Forecastsin a Flash


15/21

Reliable forecasts can have a major impact on your organization's ability to develop and implement successf

strategies. With SPSS Forecasting (formerly called SPSS Trends), you have what you need to predict trends an

develop forecasts quickly and easily.

Unlike spreadsheet programs, SPSS Forecasting has the advanced statistical techniques you need in order

work with time-series data. But you don't need to be an expert statistician to use it.

Regardless of your level of experience, you can analyze historical data and predict trends faster, and deliv

information in ways that your organization's decision makers can understand and use.

Thanks to its Expert Modeler feature, SPSS Forecasting:

Automatically determines the best-fitting ARIMA or exponential smoothing model to analyze yo

historic data

Enables you to model hundreds of different time series at once, rather than having to run the procedu

for one variable at a time

If you're new to building models from time-series data, SPSS Forcasting helps you by:

Generating reliable models, even if you're not sure how to choose exponential smoothing parameters ARIMA orders, or how to achieve stationarity

Automatically testing your data for seasonality, intermittency, and missing values, and selecti

appropriate models

Detecting outliers and preventing them from influencing parameter estimates

Generating graphs showing confidence intervals and the model's goodness of fit

If you're an experienced SPSS user Forecasting allows you to:

Control every parameter when building your data model

Or use SPSS Trends' Expert Modeler recommendations as a starting point or to check your work Key features available in SPSS Forecasting enable you to:

Save models to a central file so that forecasts can be updated when data changes, without having to r

set parameters or re-estimate the model

Write scripts so that models can be updated with new data automatically


16/21

This data chart illustrates men's clothing sales, raw and seasonally differenced over a 10-year period. Usin

seasonal difference helps to clarify the relationships within your data.


17/21

SPSS Missing Values:

Build Better Models When You Estimate Missing Data

Missing data can seriously affect your results. If you ignore missing data or assume that excluding missing data

sufficient, you risk reaching invalid and insignificant results. To ensure that you enter the data analysis stag

using data that takes missing values into account, make SPSS Missing Values (formerly called SPSS Missing Val

Analysis) part of your data management and preparation step.

SPSS Missing Values, is a critical tool for anyone concerned about data validty, including survey researcher

social scientists, data miners, and market researchers.

Uncover missing data patterns

With SPSS Missing Value Analysis, you can easily examine data from several different angles using one of s

diagnostic reports to uncover missing data patterns. You can then estimate summary statistics and impu

missing values through regression or expectation maximization algorithms (EM algorithms). SPSS Missing Val

Analysis helps you to:

Diagnose if you have a serious missing data imputation problem

Replace missing values with estimatesfor example, impute your missing data with the regression

EM algorithms

Quickly and easily diagnose your missing data

Quickly diagnose a serious missing data problem using the data patterns report, which provides a case-by-ca

overview of your data. This report helps you determine the extent of missing data; it displays a snapshot of ea

type of missing value and any extreme values for each case.

Use multiple imputation to replace missing data values

In SPSS Missing Values 17.0, a new multiple imputation procedure will help you understand patterns

missingness inyour dataset and enable you to replace missing values with plausible estimates. It offers a ful

automatic imputation mode that chooses the most suitable imputation method based on characteristics of yo

data, while also allowing you to customize your imputation model.

Several complete datasets are generated (typically, three to five), each with a different set of replaceme

values. Next, you can model the individual datasets using the usual techniques, such as linear regression, t

produce parameter estimates for each dataset. Then obtain final parameter estimates. This involves pooling t

individual sets of parameter estimates obtained in step two and computing inferential statistics that take in

account variation within and between imputations.

Analysis of the individual datasets and pooling of the results are supported via select existing IBM SPSS Statist

procedures such as REGRESSION. When operating on datasets with imputed values, existing procedures w

automatically produce pooled parameter estimates.


18/21

SPSS Neural Networks:

Find More Complex Relationships in your Data

SPSS Neural Networks offers non-linear data modeling procedures that enable you to discover more compl

relationships in your data. Using these procedures, you can develop more accurate and effective predictiv

models. The result? Deeper insight and better decision-making.

The procedures in SPSS Neural Networks complement the more traditional statistics in IBM SPSS Statistics Baand its modules. Find new associations in your data with SPSS Neural Networks and then confirm the

significance with traditional statistical techniques.

What is a neural network?

A computational neural network is a set of non-linear data modeling tools consisting of input and output laye

plus one or two hidden layers. The connections between neurons in each layer have associated weights, whic

are iteratively adjusted by the training algorithm to minimize error and provide accurate predictions.

In an MLP procedure like the one shown here, nodes in the input and output layers are connecte

to nodes in one or more hidden layers.


19/21

How can you use SPSS Neural Networks?

You can combine SPSS Neural Networks with other statistical procedures to gain clearer insight in a number

areas:

Market research

Create customer profiles

Discover customer preferences

Database marketing Segment your customer base

Optimize campaigns

Financial analysis

Analyze applicants' creditworthiness

Detect possible fraud

Operational analysis

Manage cash flow

Improve logistics planning

Healthcare

Forecast treatment costs

Perform medical outcomes analysis


20/21

SPSS Programmability Extension:

Dramatically Increase the Power and Capabilities of SPSS

Discover unlimited programming capabilities with the SPSS Programmability Extension. This powerful featu

enables your organization to extend the SPSS command syntax language with external programming language

such as Python, R, and the .NET version of Microsoft Visual Basic. The SPSS Programmability Extension

included with SPSS Base.

With the SPSS Programmability Extension, you can:

Extend SPSS functionality. The SPSS Programmability Extension enables you to add computations n

included in SPSS.

Write generalized and more flexible jobs. Create generalized jobs by controlling logic based on th

Variable Dictionary, procedure output (XML or datasets), case data, and environment. Reusable cod

means data is not tied to a single program.

Handle errors with generated exceptions. The SPSS Programmability Extension makes it easy to che

whether a long syntax job worked. Hundreds of standard modules for Python are available.

React to results and metadata Build SPSS functionality into other applications


21/21

SPSS Regression:

Improve Predictions with Powerful Nonlinear Regression Software

SPSS Regression (formerly called SPSS Regression Models) enables you to apply more sophisticated models

your data using its wide range of nonlinear regression models. You can apply SPSS Regression, to man

disciplines, including:

Market research:Study consumer buying habits Medical research:Study response to dosages through probit analysis

Institutional research:Measure academic achievement tests

Loan assessment:Analyze good and bad credit risks

SPSS Regression includes these procedures:

Multinomial logistic regression (MLR):Predict categorical outcomes with more than two categories

Binary logistic regression:Easily classify your data into two groups

Nonlinear regression (NLR) and constrained nonlinear regression (CNLR): Estimate parameters

nonlinear models Probit analysis: Evaluate the value of stimuli using a logit or probit transformation of the proportio

responding

area of spss application in manufacturing

Documents