Coverart for item
The Resource An introduction to statistics in psychology, Dennis Howitt, Duncan Cramer

An introduction to statistics in psychology, Dennis Howitt, Duncan Cramer

Label
An introduction to statistics in psychology
Title
An introduction to statistics in psychology
Statement of responsibility
Dennis Howitt, Duncan Cramer
Creator
Contributor
Subject
Language
eng
Summary
"Statistics can be difficult, but this revised 3rd edition of Introduction to Statistics in Psychology makes it much easier. Any psychology student, whether at introductory, intermediate or advanced level will find the book a very useful companion to their statistics course."--BOOK JACKET
Cataloging source
DLC
http://library.link/vocab/creatorName
Howitt, Dennis
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/relatedWorkOrContributorDate
1948-
http://library.link/vocab/relatedWorkOrContributorName
Cramer, Duncan
http://library.link/vocab/subjectName
Psychometrics
Label
An introduction to statistics in psychology, Dennis Howitt, Duncan Cramer
Instantiates
Publication
Bibliography note
Includes bibliographical references (p. [479]) and index
Contents
  • Pt. 1.
  • Descriptive statistics.
  • p. 1
  • 1.
  • Why you need statistics : types of data.
  • p. 3
  • 2.
  • Describing variables : tables and diagrams.
  • p. 8
  • 3.
  • Describing variables numerically : averages, variation and spread.
  • p. 18
  • 4.
  • Shapes of distributions of scores.
  • p. 29
  • 5.
  • Standard deviation : the standard unit of measurement in statistics.
  • p. 38
  • 6.
  • Relationships between two or more variables : diagrams and tables.
  • p. 50
  • 7.
  • Correlation coefficients : Pearson correlation and Spearman's rho.
  • p. 58
  • 8.
  • Regression : prediction with precision.
  • p. 74
  • Pt. 2.
  • Significance testing.
  • p. 85
  • 9.
  • Samples and populations : generalising and inferring.
  • p. 87
  • 10.
  • Statistical significance for the correlation coefficient : a practical introduction to statistical inference.
  • p. 93
  • 11.
  • Standard error : the standard deviation of the means of samples.
  • p. 102
  • 12.
  • t-test : comparing two samples of correlated related scores.
  • p. 108
  • 13.
  • t-test : comparing two samples of unrelated/uncorrelated scores.
  • p. 120
  • 14.
  • Chi-square : differences between samples of frequency data.
  • p. 134
  • 15.
  • Probability.
  • p. 153
  • 16.
  • Reporting significance levels succinctly.
  • p. 159
  • 17.
  • One-tailed versus two-tailed significance testing.
  • p. 164
  • 18.
  • Ranking tests : nonparametric statistics.
  • p. 168
  • Pt. 3.
  • Introduction to analysis of variance.
  • p. 179
  • 19.
  • variance ratio test : the F-ratio to compare two variances.
  • p. 181
  • 20.
  • Analysis of variance (ANOVA) : introduction to the one-way unrelated or uncorrelated ANOVA.
  • p. 187
  • 21.
  • Analysis of variance for correlated scores or repeated measures.
  • p. 204
  • 22.
  • Two-way analysis of variance for unrelated/uncorrelated scores : two experiments for the price of one?.
  • p. 220
  • 23.
  • Multiple comparisons in ANOVA : just where do the differences lie?.
  • p. 247
  • 24.
  • More analysis of variance designs : mixed-design ANOVA and analysis of covariance (ANCOVA).
  • p. 255
  • 25.
  • Statistics and the analysis of experiments.
  • p. 283
  • Pt. 4.
  • More advanced correlational statistics.
  • p. 289
  • 26.
  • Partial correlation : spurious correlation, third or confounding variables, suppressor variables.
  • p. 291
  • 27.
  • Factor analysis : simplifying complex data.
  • p. 300
  • 28.
  • Multiple regression and multiple correlation.
  • p. 316
  • 29.
  • Path analysis.
  • p. 329
  • 30.
  • analysis of a questionnaire/survey project.
  • p. 341
  • Pt. 5.
  • Assorted advanced techniques.
  • p. 349
  • 31.
  • Statistical power analysis : do my findings matter?.
  • p. 351
  • 32.
  • Meta-analysis : combining and exploring statistical findings from previous research.
  • p. 358
  • 33.
  • Reliability in scales and measurement : consistency and agreement.
  • p. 375
  • 34.
  • Confidence intervals.
  • p. 386
  • Pt. 6.
  • Advanced qualitative or nominal techniques.
  • p. 395
  • 35.
  • analysis of complex contingency tables : log-linear methods.
  • p. 397
  • 36.
  • Multinomial logistic regression : distinguishing between several different categories or groups.
  • p. 419
  • 37.
  • Binomial logistic regression.
  • p. 433
Control code
ocm56880351
Dimensions
25 cm.
Edition
3rd ed.
Extent
xxiii, 488 p.
Isbn
9780131399853
Lccn
2004060094
Other physical details
ill.
Label
An introduction to statistics in psychology, Dennis Howitt, Duncan Cramer
Publication
Bibliography note
Includes bibliographical references (p. [479]) and index
Contents
  • Pt. 1.
  • Descriptive statistics.
  • p. 1
  • 1.
  • Why you need statistics : types of data.
  • p. 3
  • 2.
  • Describing variables : tables and diagrams.
  • p. 8
  • 3.
  • Describing variables numerically : averages, variation and spread.
  • p. 18
  • 4.
  • Shapes of distributions of scores.
  • p. 29
  • 5.
  • Standard deviation : the standard unit of measurement in statistics.
  • p. 38
  • 6.
  • Relationships between two or more variables : diagrams and tables.
  • p. 50
  • 7.
  • Correlation coefficients : Pearson correlation and Spearman's rho.
  • p. 58
  • 8.
  • Regression : prediction with precision.
  • p. 74
  • Pt. 2.
  • Significance testing.
  • p. 85
  • 9.
  • Samples and populations : generalising and inferring.
  • p. 87
  • 10.
  • Statistical significance for the correlation coefficient : a practical introduction to statistical inference.
  • p. 93
  • 11.
  • Standard error : the standard deviation of the means of samples.
  • p. 102
  • 12.
  • t-test : comparing two samples of correlated related scores.
  • p. 108
  • 13.
  • t-test : comparing two samples of unrelated/uncorrelated scores.
  • p. 120
  • 14.
  • Chi-square : differences between samples of frequency data.
  • p. 134
  • 15.
  • Probability.
  • p. 153
  • 16.
  • Reporting significance levels succinctly.
  • p. 159
  • 17.
  • One-tailed versus two-tailed significance testing.
  • p. 164
  • 18.
  • Ranking tests : nonparametric statistics.
  • p. 168
  • Pt. 3.
  • Introduction to analysis of variance.
  • p. 179
  • 19.
  • variance ratio test : the F-ratio to compare two variances.
  • p. 181
  • 20.
  • Analysis of variance (ANOVA) : introduction to the one-way unrelated or uncorrelated ANOVA.
  • p. 187
  • 21.
  • Analysis of variance for correlated scores or repeated measures.
  • p. 204
  • 22.
  • Two-way analysis of variance for unrelated/uncorrelated scores : two experiments for the price of one?.
  • p. 220
  • 23.
  • Multiple comparisons in ANOVA : just where do the differences lie?.
  • p. 247
  • 24.
  • More analysis of variance designs : mixed-design ANOVA and analysis of covariance (ANCOVA).
  • p. 255
  • 25.
  • Statistics and the analysis of experiments.
  • p. 283
  • Pt. 4.
  • More advanced correlational statistics.
  • p. 289
  • 26.
  • Partial correlation : spurious correlation, third or confounding variables, suppressor variables.
  • p. 291
  • 27.
  • Factor analysis : simplifying complex data.
  • p. 300
  • 28.
  • Multiple regression and multiple correlation.
  • p. 316
  • 29.
  • Path analysis.
  • p. 329
  • 30.
  • analysis of a questionnaire/survey project.
  • p. 341
  • Pt. 5.
  • Assorted advanced techniques.
  • p. 349
  • 31.
  • Statistical power analysis : do my findings matter?.
  • p. 351
  • 32.
  • Meta-analysis : combining and exploring statistical findings from previous research.
  • p. 358
  • 33.
  • Reliability in scales and measurement : consistency and agreement.
  • p. 375
  • 34.
  • Confidence intervals.
  • p. 386
  • Pt. 6.
  • Advanced qualitative or nominal techniques.
  • p. 395
  • 35.
  • analysis of complex contingency tables : log-linear methods.
  • p. 397
  • 36.
  • Multinomial logistic regression : distinguishing between several different categories or groups.
  • p. 419
  • 37.
  • Binomial logistic regression.
  • p. 433
Control code
ocm56880351
Dimensions
25 cm.
Edition
3rd ed.
Extent
xxiii, 488 p.
Isbn
9780131399853
Lccn
2004060094
Other physical details
ill.

Library Locations

    • Brunswick Library StoreBorrow it
      Liverpool, GB
Processing Feedback ...