Statistics Explained

Front Cover
Routledge, Mar 21, 2014 - Psychology - 376 pages

Statistics Explained is an accessible introduction to statistical concepts and ideas. It makes few assumptions about the reader’s statistical knowledge, carefully explaining each step of the analysis and the logic behind it. The book:

  • provides a clear explanation of statistical analysis and the key statistical tests employed in analysing research data

  • gives accessible explanations of how and why statistical tests are used

  • includes a wide range of practical, easy-to-understand worked examples.

Building on the international success of earlier editions, this fully updated revision includes developments in statistical analysis, with new sections explaining concepts such as bootstrapping and structural equation modelling. A new chapter - ‘Samples and Statistical Inference’ - explains how data can be analysed in detail to examine its suitability for certain statistical tests.

The friendly and straightforward style of the text makes it accessible to all those new to statistics, as well as more experienced students requiring a concise guide. It is suitable for students and new researchers in disciplines including Psychology, Education, Sociology, Sports Science, Nursing, Communication, and Media and Business Studies.

Presented in full colour and with an updated, reader-friendly layout, this new edition also comes with a companion website featuring supplementary resources for students. Unobtrusive cross-referencing makes it the ideal companion to Perry R. Hinton’s SPSS Explained, also published by Routledge.

Perry R. Hinton has many years of experience in teaching statistics to students from a wide range of disciplines and his understanding of the problems students face forms the basis of this book.

 

Contents

List of figures
Linear correlation and regression
Descriptive statistics
Standard scores
Introduction to hypothesis testing
Sampling
Hypothesis testing with one sample
Selecting samples for comparison
The two factor ANOVA
Two sample nonparametric analysis
One factor ANOVA for ranked data
chisquare
Multiple correlation and regression
Complex analyses
An introduction to the general linear model
Postscript

Hypothesis testing with two samples
Significance error and power
Samples and statistical inference
Introduction to the analysis of variance
One factor independent ANOVA
Multiple comparisons
The interaction of factors in the analysis of variance
Critical Values of the F Distribution A 4 Critical Values of the Studentized Range Statistic q A 5 Critical Values of the MannWhitney U Statistic A 6 C...
Critical Values of the ChiSquare χ2 Distribution A 8 Table of Probabilities for χr2 when k and n are Small A 9 Critical Values of the Pearson r Correl...
Glossary
References
Index
Copyright

Other editions - View all

Statistics Explained
Perry R. Hinton
Limited preview - 2014
Statistics Explained
Perry R. Hinton
No preview available - 2014
Statistics Explained
Perry Roy Hinton
No preview available - 2014

Common terms and phrases

a z score analysis of variance ANOVA assumption bootstrap samples calculated value cent Chapter Recap confidence interval correlation critical value Cyadmine degrees of freedom dferror estimate examination marks example F distribution F value Figure formula frequency distribution hothousing hypothesis is true hypothesis testing independent measures independent variable indicates interaction known distribution kurtosis level of significance linear model look Mean square median multiple comparisons null hypothesis number of conditions number of scores one-tailed test participants pcomp population mean probability produce quartile random errors range reject the null repeated measures residuals sample means sample standard deviation sample statistics sampling distribution significance level significant difference simple main effects skew SPSS SSbet.conds standard error standard normal distribution statistical analysis statistical tests sums of squares systematic differences table value two-tailed prediction two-tailed test Type I error usual-IQ distribution Variance ratio variation zero

About the author (2014)

Perry R. Hinton is a psychologist, and has worked for over twenty-five years in four British universities, in positions ranging from lecturer to Head of Department. He has taught in the areas of cognitive and social psychology, and research methods and statistics, primarily to psychology and communication and media students; but also to a wide range of students studying subjects including nursing, social work, linguistics, philosophy and education. He has written four textbooks and edited the Psychology Focus series for Routledge.

Bibliographic information

TitleStatistics Explained
AuthorPerry R. Hinton
Edition3, illustrated, revised
PublisherRoutledge, 2014
ISBN1317753917, 9781317753919
Length376 pages
Subjects › 

Psychology / General
Psychology / Statistics
  
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