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The Resource An introduction to statistics in psychology, Dennis Howitt and Duncan Cramer

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

Label
An introduction to statistics in psychology
Title
An introduction to statistics in psychology
Statement of responsibility
Dennis Howitt and Duncan Cramer
Creator
Contributor
Subject
Language
eng
Cataloging source
DLC
http://library.link/vocab/creatorName
Howitt, Dennis
Illustrations
illustrations
Index
index present
Literary form
non fiction
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 and Duncan Cramer
Instantiates
Publication
Bibliography note
Includes bibliographical references (p. 475-476) and index
Contents
  • Introduction
  • Pt. 1.
  • Descriptive statistics.
  • p. 1
  • 1.
  • Why you need statistics: Types of data.
  • p. 3
  • 2.
  • Describing variables: Tables and diagrams.
  • p. 9
  • 3.
  • Describing variables numerically: Averages, variation and spread.
  • p. 20
  • 4.
  • Shapes of distributions of scores.
  • p. 31
  • 5.
  • Standard deviation: The standard unit of measurement in statistics.
  • p. 41
  • 6.
  • Relationships between two or more variables: Diagrams and tables.
  • p. 53
  • 7.
  • Correlation coefficients: Pearson correlation and Spearman's rho.
  • p. 62
  • 8.
  • Regression: Prediction with precision.
  • p. 80
  • Pt. 2.
  • Significance testing.
  • p. 91
  • 9.
  • Samples and populations: Generalising and inferring.
  • p. 93
  • 10.
  • Statistical significance for the correlation coefficient: A practical introduction to statistical inference.
  • p. 99
  • 11.
  • Standard error: The standard deviation of the means of samples.
  • p. 109
  • 12.
  • t-test: Comparing two samples of correlated/related scores.
  • p. 115
  • 13.
  • t-test: Comparing two groups of unrelated/uncorrelated scores.
  • p. 127
  • 14.
  • Chi-square: Differences between samples of frequency data.
  • p. 142
  • 15.
  • Probability.
  • p. 161
  • 16.
  • Reporting significance levels succinctly.
  • p. 167
  • 17.
  • One-tailed versus two-tailed significance testing.
  • p. 172
  • 18.
  • Ranking tests: nonparametric statistics.
  • p. 176
  • Pt. 3.
  • Introduction to analysis of variance.
  • p. 187
  • 19.
  • variance ratio test: The F-ratio to compare two variances.
  • p. 189
  • 20.
  • Analysis of variance (ANOVA): Introduction to the one-way unrelated or uncorrelated ANOVA.
  • p. 195
  • 21.
  • Analysis of variance for correlated scores or repeated measures.
  • p. 214
  • 22.
  • Two-way analysis of variance for unrelated/uncorrelated scores: Two experiments for the price of one?.
  • p. 231
  • 23.
  • Multiple comparisons in ANOVA: Just where do the differences lie?.
  • p. 262
  • 24.
  • More analysis of variance designs: Mixed-design ANOVA and analysis of covariance (ANCOVA).
  • p. 269
  • 25.
  • Statistics and the analysis of experiments.
  • p. 300
  • Pt. 4.
  • More advanced correlational statistics.
  • p. 307
  • 26.
  • Partial correlation: Spurious correlation, third variables, suppressor variables.
  • p. 309
  • 27.
  • Factor analysis: simplifying complex data.
  • p. 319
  • 28.
  • Multiple regression and multiple correlation.
  • p. 334
  • 29.
  • Path analysis.
  • p. 346
  • 30.
  • analysis of a questionnaire/survey project.
  • p. 360
  • Pt. 5.
  • Assorted advanced techniques.
  • p. 369
  • 31.
  • Statistical power analysis: Do my findings matter?.
  • p. 371
  • 32.
  • Meta-analysis: Combining and exploring statistical findings from previous research.
  • p. 378
  • 33.
  • Reliability in scales and measurement: Consistency and agreement.
  • p. 396
  • 34.
  • Confidence intervals.
  • p. 407
  • 35.
  • analysis of complex contingency tables: Log-linear methods.
  • p. 416
  • App. A.
  • Testing for excessively skewed distributions.
  • p. 442
  • App. B1.
  • Large sample formulae for the nonparametric tests.
  • p. 445
  • App. B2.
  • Nonparametric tests for three or more groups.
  • p. 446
  • App. C.
  • Extended table of significance for the Pearson correlation coefficient.
  • p. 450
  • App. D.
  • Table of significance for the Spearman correlation coefficient.
  • p. 453
  • App. E.
  • Extended table of significance for the t-test.
  • p. 456
  • App. F.
  • Table of significance for chi-square.
  • p. 459
  • App. G.
  • Extended table of significance for the sign test.
  • p. 460
  • App. H.
  • Table of significance for the Wilcoxon Matched Pairs Test.
  • p. 463
  • App. I.
  • Table of significance for the Mann-Whitney U-test.
  • p. 466
  • App. J.
  • Table of significant values for the F-distribution.
  • p. 468
  • App. K.
  • Table of significant values of t when making multiple t-tests.
  • p. 472
  • References.
  • p. 475
  • Index.
  • p. 477
Control code
l82002030773
Dimensions
24 cm.
Edition
Rev. 2nd ed
Extent
xii, 482 p.
Isbn
9780131399822
Lccn
2002030773
Other physical details
ill
Label
An introduction to statistics in psychology, Dennis Howitt and Duncan Cramer
Publication
Bibliography note
Includes bibliographical references (p. 475-476) and index
Contents
  • Introduction
  • Pt. 1.
  • Descriptive statistics.
  • p. 1
  • 1.
  • Why you need statistics: Types of data.
  • p. 3
  • 2.
  • Describing variables: Tables and diagrams.
  • p. 9
  • 3.
  • Describing variables numerically: Averages, variation and spread.
  • p. 20
  • 4.
  • Shapes of distributions of scores.
  • p. 31
  • 5.
  • Standard deviation: The standard unit of measurement in statistics.
  • p. 41
  • 6.
  • Relationships between two or more variables: Diagrams and tables.
  • p. 53
  • 7.
  • Correlation coefficients: Pearson correlation and Spearman's rho.
  • p. 62
  • 8.
  • Regression: Prediction with precision.
  • p. 80
  • Pt. 2.
  • Significance testing.
  • p. 91
  • 9.
  • Samples and populations: Generalising and inferring.
  • p. 93
  • 10.
  • Statistical significance for the correlation coefficient: A practical introduction to statistical inference.
  • p. 99
  • 11.
  • Standard error: The standard deviation of the means of samples.
  • p. 109
  • 12.
  • t-test: Comparing two samples of correlated/related scores.
  • p. 115
  • 13.
  • t-test: Comparing two groups of unrelated/uncorrelated scores.
  • p. 127
  • 14.
  • Chi-square: Differences between samples of frequency data.
  • p. 142
  • 15.
  • Probability.
  • p. 161
  • 16.
  • Reporting significance levels succinctly.
  • p. 167
  • 17.
  • One-tailed versus two-tailed significance testing.
  • p. 172
  • 18.
  • Ranking tests: nonparametric statistics.
  • p. 176
  • Pt. 3.
  • Introduction to analysis of variance.
  • p. 187
  • 19.
  • variance ratio test: The F-ratio to compare two variances.
  • p. 189
  • 20.
  • Analysis of variance (ANOVA): Introduction to the one-way unrelated or uncorrelated ANOVA.
  • p. 195
  • 21.
  • Analysis of variance for correlated scores or repeated measures.
  • p. 214
  • 22.
  • Two-way analysis of variance for unrelated/uncorrelated scores: Two experiments for the price of one?.
  • p. 231
  • 23.
  • Multiple comparisons in ANOVA: Just where do the differences lie?.
  • p. 262
  • 24.
  • More analysis of variance designs: Mixed-design ANOVA and analysis of covariance (ANCOVA).
  • p. 269
  • 25.
  • Statistics and the analysis of experiments.
  • p. 300
  • Pt. 4.
  • More advanced correlational statistics.
  • p. 307
  • 26.
  • Partial correlation: Spurious correlation, third variables, suppressor variables.
  • p. 309
  • 27.
  • Factor analysis: simplifying complex data.
  • p. 319
  • 28.
  • Multiple regression and multiple correlation.
  • p. 334
  • 29.
  • Path analysis.
  • p. 346
  • 30.
  • analysis of a questionnaire/survey project.
  • p. 360
  • Pt. 5.
  • Assorted advanced techniques.
  • p. 369
  • 31.
  • Statistical power analysis: Do my findings matter?.
  • p. 371
  • 32.
  • Meta-analysis: Combining and exploring statistical findings from previous research.
  • p. 378
  • 33.
  • Reliability in scales and measurement: Consistency and agreement.
  • p. 396
  • 34.
  • Confidence intervals.
  • p. 407
  • 35.
  • analysis of complex contingency tables: Log-linear methods.
  • p. 416
  • App. A.
  • Testing for excessively skewed distributions.
  • p. 442
  • App. B1.
  • Large sample formulae for the nonparametric tests.
  • p. 445
  • App. B2.
  • Nonparametric tests for three or more groups.
  • p. 446
  • App. C.
  • Extended table of significance for the Pearson correlation coefficient.
  • p. 450
  • App. D.
  • Table of significance for the Spearman correlation coefficient.
  • p. 453
  • App. E.
  • Extended table of significance for the t-test.
  • p. 456
  • App. F.
  • Table of significance for chi-square.
  • p. 459
  • App. G.
  • Extended table of significance for the sign test.
  • p. 460
  • App. H.
  • Table of significance for the Wilcoxon Matched Pairs Test.
  • p. 463
  • App. I.
  • Table of significance for the Mann-Whitney U-test.
  • p. 466
  • App. J.
  • Table of significant values for the F-distribution.
  • p. 468
  • App. K.
  • Table of significant values of t when making multiple t-tests.
  • p. 472
  • References.
  • p. 475
  • Index.
  • p. 477
Control code
l82002030773
Dimensions
24 cm.
Edition
Rev. 2nd ed
Extent
xii, 482 p.
Isbn
9780131399822
Lccn
2002030773
Other physical details
ill

Library Locations

    • Brunswick Library StoreBorrow it
      Liverpool, GB
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