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Handbook of Univariate and Multivariate Data Analysis with IBM SPSS

Robert Ho
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A01=Robert Ho
advanced multivariate analysis applications
ANOVA Output
Author_Robert Ho
bar
canonical correlation
Category=PBT
Category=UFM
data analysis in the social sciences
data analysis using SPSS
data imputation techniques
Data Set
dependent
entry
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
experimental design
explore
Explore Window
factor analysis
format
General Linear Model
GLM Multivariate Analysis
GPA Score
Grade Point Average
Group Invariant Model
Group Variable
Hotelling's Trace
Hotelling’s Trace
how to apply statistical tests to experimental findings
how to deal with missing data
hypothesis
implementing univariate and multivariate statistical tests
Linear Regression Window
logistic regression
Lower Bound Upper Bound
menu
multiple discriminant analysis
Multivariate Tests
Multivariate Testsb
path analysis
Pillai's Trace
Pillai’s Trace
Post Hoc Comparisons
Prediction Equation
Predictor Variables
psychometrics
quantitative research methods
Roy's Largest Root
Roy’s Largest Root
Sav
social science statistics
SPSS Output
SPSS Syntax Method
Standardized Regression Weights
statistical significance testing
structural equation modeling
tests of assumptions
variable
Voluntary Euthanasia
window
Windows Method

Product details

  • ISBN 9781032477442
  • Weight: 900g
  • Dimensions: 156 x 234mm
  • Publication Date: 21 Jan 2023
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Description

Using the same accessible, hands-on approach as its best-selling predecessor, the Handbook of Univariate and Multivariate Data Analysis with IBM SPSS, Second Edition explains how to apply statistical tests to experimental findings, identify the assumptions underlying the tests, and interpret the findings. This second edition now covers more topics and has been updated with the SPSS statistical package for Windows.

New to the Second Edition



  • Three new chapters on multiple discriminant analysis, logistic regression, and canonical correlation


  • New section on how to deal with missing data


  • Coverage of tests of assumptions, such as linearity, outliers, normality, homogeneity of variance-covariance matrices, and multicollinearity


  • Discussions of the calculation of Type I error and the procedure for testing statistical significance between two correlation coefficients obtained from two samples


  • Expanded coverage of factor analysis, path analysis (test of the mediation hypothesis), and structural equation modeling


Suitable for both newcomers and seasoned researchers in the social sciences, the handbook offers a clear guide to selecting the right statistical test, executing a wide range of univariate and multivariate statistical tests via the Windows and syntax methods, and interpreting the output results. The SPSS syntax files used for executing the statistical tests can be found in the appendix. Data sets employed in the examples are available on the book’s CRC Press web page.

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