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Data Analysis with IBM SPSS Statistics

You're reading from  Data Analysis with IBM SPSS Statistics

Product type Book
Published in Sep 2017
Publisher Packt
ISBN-13 9781787283817
Pages 446 pages
Edition 1st Edition
Languages
Authors (2):
Ken Stehlik-Barry Ken Stehlik-Barry
Profile icon Ken Stehlik-Barry
Anthony Babinec Anthony Babinec
Profile icon Anthony Babinec
View More author details
Toc

Table of Contents (17) Chapters close

Preface 1. Installing and Configuring SPSS 2. Accessing and Organizing Data 3. Statistics for Individual Data Elements 4. Dealing with Missing Data and Outliers 5. Visually Exploring the Data 6. Sampling, Subsetting, and Weighting 7. Creating New Data Elements 8. Adding and Matching Files 9. Aggregating and Restructuring Data 10. Crosstabulation Patterns for Categorical Data 11. Comparing Means and ANOVA 12. Correlations 13. Linear Regression 14. Principal Components and Factor Analysis 15. Clustering 16. Discriminant Analysis

Matching the aggregated file back to find specific records

Another use of this file is to match it back to the invoice-level file to find the invoice corresponding to the customer's largest purchase during the time covered by this data. Starting with the invoice-level file as the active dataset, the following dialog box shows how to use the customer-level file as a lookup table to get the information associated with the largest invoice:

CustomerID serves as the match key in this one-to-many match. The * and + symbols indicate which file was the source for each of the variables in the resulting file.

The SPSS syntax to perform this match is shown here along with the transformation commands used to identify the largest invoice for each customer:

STAR JOIN
/SELECT t0.InvoiceNo, t0.InvoiceDate, t0.itemcost_total, t0.numproducts, t0.priorinvoicedate,
t0.priorcustID, t0.daysincepurchase...
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