Discover a large selection of styles New White Mercurials and Soccer Cleats Mercurial Superfly,go now.

Multivariate Data Analysis  Sixth Edition by Hair, Black, Babin, Anderson and Tatham

Multivariate Data Analysis by Hair, et al  -- The world's leading authority on applied multivariate data analysis based on number of citations, as reported by Google Scholar


A number of datasets are available to enable students and faculty to perform the multivariate analyses described in the textbook.  While some techniques require specialized datasets (e.g., multidimensional scaling, conjoint analysis and structural equation modeling), many of the techniques are performed using conventional survey data. 


Download All Datasets and Documentation in a Single File
Download All Datasets in EXCEL format
Dataset Documentation (PDF file)


Individual Datasets (in SPSS .SAV format)

HBAT:  Actually a series of datasets used with many of the techniques.





Download the set of four datasets or individual datasets.

HBAT: the primary database with multiple metric & nonmetric variables allowing for use in most of the multivariate techniques. HBAT_200: an expanded dataset, comparable to HBAT except for 200 rather than 100 respondents, used in MANOVA.
HBAT_MISSING; a reduced dataset with 70 respondents and missing data in the variables.  Used with techniques for diagnosis and remedy of missing data (Chapter 2). HBAT_SPLITS: contains two variables that split the HBAT dataset into 50/50 and 60/40 subsamples.  This dataset can be merged with the original HBAT dataset if desired.
Conjoint Analysis HBAT_CPLAN: details the "full-profile" stimulus descriptions HBAT_CONJOINT: contains the actual responses to the stimulus profiles


HBAT_MDS: used in MDS (multidimensional scaling) HBAT_CORRESP: used for correspondence analysis
Structural Equation

Modeling (SEM)


Download the set of five datasets or individual datasets.

HBAT_SEM: the original data responses from 400 individuals used to derive the input matrices for SEM programs (e.g. LISREL, EQS or AMOS) HBAT_SEM_NOMISSING: the original dataset of 400 responses has two individuals with missing data.  This dataset replaces the missing values so that the resulting sample is 400 complete responses.
HBAT.COV, HBATF.COV and HBATM.COV: these three covariance matrices represent the overall sample, female respondents and male respondents, respectively.
Other Datasets:
Two additional datasets are provided to allow students access to data other than the HBAT data files described in the textbook HATCO: this dataset has been utilized in past versions of the textbook and provides a simplified set of variables amenable to all of the basic multivariate techniques. SALES: this dataset concerns sales training and is comprised of 80 respondents, representing a portion of data that was collected by academic researcher

Drop us an e-mail if you have a comment, suggestion
or online resource you would like to share.


Multivariate Data Analysis  6/E
Hair, Black, Babin, Anderson and Tatham