MARC record from Internet Archive

LEADER: 08883cam 2200709 i 4500
001 ocn856879212
003 OCoLC
005 20211029084746.0
008 130822s2014 enka b 001 0 eng
010 $a 2013032712
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015 $aGBB403701$2bnb
016 7 $a016598477$2Uk
016 7 $a016598478$2Uk
019 $a859584966
020 $a9781848723115$q(alk. paper)
020 $a1848723113$q(alk. paper)
020 $a9781848723122$q(alk. paper)
020 $a1848723121$q(alk. paper)
020 $z9781315797564$q(ebk.)
020 $z1315797569$q(ebk.)
020 $z9781317753919 (ePub ebook)
020 $z9781317753926 (PDF ebook)
020 $z9781317753902 (Mobipocket ebook)
035 $a(OCoLC)856879212$z(OCoLC)859584966
042 $apcc
050 00 $aBF39$b.H54 2014
082 00 $a519.5$223
100 1 $aHinton, Perry R.$q(Perry Roy),$d1954-
245 10 $aStatistics explained /$cPerry R. Hinton.
250 $aThird edition.
264 1 $aLondon ;$aNew York :$bRoutledge, Taylor & Francis Group,$c2014.
300 $axvii, 357 pages :$billustrations ;$c25 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
338 $avolume$bnc$2rdacarrier
504 $aIncludes bibliographical references (page 351) and index.
505 0 $aIntroduction -- Descriptive statistics -- Standard scores -- Introduction to hypothesis testing -- Sampling -- Hypothesis testing with one sample -- Selecting samples for comparison -- 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 -- One factor repeated measures ANOVA -- The interaction of factors in the analysis of variance -- The two factor ANOVA -- Two sample nonparametric analysis -- One factor ANOVA for ranked data -- Analysing frequency data : chi-square -- Linear correlation and regression -- Multiple correlation and regression -- Complex analyses -- An introduction to the general linear model -- Postscript.
520 $a"Statistics Explained is an accessible introduction to statistical concepts and ideas. It makes few assumptions about the readers statistical knowledge, carefully explaining each step of the analysis and the logic behind it." -- Amazon.com.
650 0 $aPsychometrics.
650 02 $aStatistics as Topic.
650 02 $aSocial Sciences$xmethods.
650 7 $aPsychometrics.$2fast$0(OCoLC)fst01081639
650 7 $aStatistik$2gnd
655 7 $aStatistics.$2fast$0(OCoLC)fst01423727
655 7 $aStatistics.$2lcgft
880 00 $6505-00/(S$aMachine generated contents note:$gch. 1$tIntroduction --$tAccompanying Website --$gch. 2$tDescriptive Statistics --$tMeasures Of 'Central Tendency' --$tMeasures Of 'Spread' --$tDescribing A Set Of Data: In Conclusion --$tComparing Two Sets Of Data With Descriptive Statistics --$tSome Important Information About Numbers --$tChapter Recap --$gch. 3$tStandard Scores --$tComparing Scores From Different Distributions --$tThe Normal Distribution --$tThe Standard Normal Distribution --$tChapter Recap --$gch. 4$tIntroduction To Hypothesis Testing --$tTesting A Hypothesis --$tOne- And Two-Tailed Predictions --$tChapter Recap --$gch. 5$tSampling --$tPopulations And Samples --$tSelecting A Sample --$tSample Statistics And Population Parameters --$tChapter Recap --$gch. 6$tHypothesis Testing With One Sample --$tAn Example --$tWhen We Do Not Have The Known Population Standard Deviation --$tConfidence Intervals --$tChapter Recap --$gch. 7$tSelecting Samples For Comparison --$tComparing Samples --$tThe Interpretation Of Sample Differences --$tChapter Recap --$gch. 8$tHypothesis Testing With Two Samples --$tThe Assumptions Of The Two Sample t Test --$tPaired Samples Or Independent Samples --$tThe Paired Samples (Related) t Test --$tThe Independent t Test --$tChapter Recap --$gch. 9$tSignificance, Error And Power --$tType I And Type II Errors --$tStatistical Power --$tThe Power Of A Test --$tThe Choice Of A Level --$tEffect Size --$tSample Size --$tChapter Recap --$gch. 10$tSamples And Statistical Inference --$tExamining A Sample --$tNormally Distributed Populations And Samples --$tSkew --$tKurtosis --$tTests Of Normality --$tOutliers --$tSample Variation --$tParametric Tests And Measurement --$tBootstrapping --$tChapter Recap --$gch. 11$tIntroduction To The Analysis Of Variance --$tFactors And Conditions --$tThe Limitations Of The Ttest --$tWhy Do Scores Vary In A Set Of Data--$tThe Process Of Analysing Variability --$tThe F Distribution --$tChapter Recap --$gch. 12$tOne Factor Independent Anova --$tAnalysing Variability In The Independent Anova --$tRejecting The Null Hypothesis --$tUnequal Sample Sizes --$tThe Relationship Of F To t --$tChapter Recap --$gch. 13$tMultiple Comparisons --$tThe Tukey Test (For All Pairwise Comparisons) --$tThe Scheffe Test (For Complex Comparisons) --$tChapter Recap --$gch. 14$tOne Factor Repeated Measures Anova --$tDeriving The F Value --$tMultiple Comparisons --$tChapter Recap --$gch. 15$tThe Interaction Of Factors In The Analysis Of Variance --$tInteractions --$tDividing Up The Between Conditions Sums Of Squares --$tSimple Main Effects --$tChapter Recap --$gch. 16$tThe Two Factor Anova --$tThe Two Factor Independent Anova --$tThe Two Factor Mixed Design Anova --$tThe Two Factor Repeated Measures Anova --$tA Non-Significant Interaction --$tChapter Recap --$gch. 17$tTwo Sample Nonparametric Analysis --$tOrdinal Data --$tCalculating Ranks --$tThe Mann--Whitney U Test (For Independent Samples) --$tThe Wilcoxon Signed-Ranks Test (For Paired Samples) --$tChapter Recap --$gch. 18$tOne Factor Anova For Ranked Data --$tKruskal--Wallis Test (For Independent Measures) --$tThe Friedman Test (For Related Samples) --$tChapter Recap --$gch. 19$tAnalysing Frequency Data: Chi-Square --$tNominal Data, Categories And Frequency Counts --$tIntroduction To Χ2 --$tChi-Square (Χ2) As A 'Goodness Of Fit' Test --$tChi-Square (Χ2) As A Test Of Independence --$tThe Chi-Square Distribution --$tThe Assumptions Of The Χ2 Test --$tChapter Recap --$gch. 20$tLinear Correlation And Regression --$tIntroduction --$tPearson r Correlation Coefficient --$tLinear Regression --$tThe Interpretation Of Correlation And Regression --$tProblems With Correlation And Regression --$tThe Standard Error Of The Estimate --$tThe Spearman rs Correlation Coefficient --$tChapter Recap --$gch. 21$tMultiple Correlation And Regression --$tIntroduction To Multivariate Analysis --$tPartial Correlation --$tMultiple Correlation --$tMultiple Regression --$tThe Significance Of R2 --$tChapter Recap --$gch. 22$tComplex Analyses --$tComplex Analyses And The Analysis Of Variation --$tReliability --$tFactor Analysis --$tMultivariate Analysis Of Variance (Manova) --$tDiscriminant Function Analysis --$tStructural Equation Modelling --$tChapter Recap --$gch. 23$tAn Introduction To The General Linear Model --$tModels --$tAn Example Of A Linear Model --$tModelling Data --$tThe Model: The Regression Equation --$tSelecting A Good Model --$tComparing Samples (The Analysis Of Variance Once Again) --$tExplaining Variations In The Data --$tThe General Linear Model --$tChapter Recap --$gch. 24$tPostscript --$tAppendix: Acknowledgements And Statistical Tables --$gA.1.$tThe standard normal distribution tables --$gA.2.$tCritical values of the t distribution --$gA.3.$tCritical values of the F distribution --$gA.4.$tCritical values of the Studentized range statistic, q --$gA.5.$tCritical values of the Mann--Whitney U statistic --$gA.6.$tCritical values of the Wilcoxon T statistic --$gA.7.$tCritical values of the chi-square (Χ2) distribution --$gA.8.$tTable of probabilities for Χ2r when k and n are small --$gA.9.$tCritical values of the Pearson r correlation coefficient --$gA.10.$tCritical values of the Spearman rs ranked correlation coefficient --$gA.11.$tExcel commands for the D'Agostino--Pearson omnibus K2 test.
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