Davis Cole. SPSS for applied sciences. Basic statistical testing

Australia: CSIRO Publishing, 2013. — VI, 175 p.This book assumes that many applied researchers, scientific or otherwise, will not want to use statistical equations or to learn about a range of arcane statistical concepts. Instead, it is a very practical, easy and speedy introduction to data analysis in the round, offering examples from a range of scenarios from applied science, handling both continuous and rough-hewn data sets.
Examples will be found from agriculture, arboriculture, audiology, biology, computer science, ecology, engineering, epidemiology, farming a farm management, hydrology, medicine, ophthalmology, pharmacology, physiotherapy, spectroscopy and sports science.Pre-test considerationsWhat this book does
The organisation of content
Data sets and additional informationHow to use this bookDescriptive and inferential statistics introduced
Descriptive statistics
Inferential statisticsParamrtric and non-parametric tests
Different types of data
Parametric versus non-parametric dataUsing SPSS
Data entry in spreadsheet formats
Data entry with SPSSPractical research
Data analysis in context
Notes on research design
A suggestion for data analysis structure
Selecting cases
Other data manipulation techniquesUsing the statistical testsExperements and quasi-experements
The analysis of differences
Unrelated and related design
Two or more conditions
Data type
Research design terminology
Different subjects, two conditions
Different subjects, more than two conditions
Same subjects, two conditions
Same subjects, more than two conditions
Factorial ANOVA
Reading factorial ANOVA charts
Multiple comparisonsFrequency of observations
Dichotomies: the binomial test
Repeated dichonomies: the McNemar test
More than two conditions: Chi-square goodnes of fit test
Customising expected values: Chi-square goodness of fit
Relationships between variables: Chi-square test of associationThe time until events
Statistical assumptions
The Kaplan — Meier survival function
The life tableCorrelations, regression and factor analysis
Correlation
Regression
Partial correlation: 'partialling out'
The multiple correlation matrix
Factor analysis: a data reduction methodologyMiscellaneousExercises
Questions
AnswersReporting in applied settings
Raw data or central tendency?
Charts
Written reporting
Verbal reportingAdvanced statistical techniques: a tester
MANOVA
Cluster analysis
Logistic regression
Cox's regression (aka the Cox model)
Some thoughts on ANCOVAReferences
Index