Understanding statistics for the social sciences with IBM SPSS

Content: PrefaceAbout the authorIntroduction to the Scientific Methodology of ResearchIntroductionThe scientific approach versus the layperson\'s approachto knowledgeSamplingResearch designsBetween-groups designThe univariate approachThe multivariate approachCorrelational designHypothesis testing and probability theoryProbabilityStatistics and scientific researchDefinition of statisticsDescriptive statisticsInferential statisticsIntroduction to SPSSLearning how to use the SPSS software program.Introduction to SPSSSetting up a data filePreparing a code-bookData setCreating SPSS data fileData entrySaving and editing data fileSPSS analysis: Windows method versus syntax methodSPSS analysis: Windows methodSPSS analysis: Syntax methodSPSS outputResults and interpretationDESCRIPTIVE STATISTICSBasic mathematical concepts and measurementBasic mathematical conceptsMathematical notationsMeasurement scales (levels of measurement)Nominal scalesOrdinal scalesInterval scalesRatio scalesTypes of variablesIndependent and dependent variablesContinuous and discrete variablesReal limits of continuous variablesRoundingFrequency distributionsUngrouped frequency distributionsSPSS: Data entry formatSPSS Windows methodSPSS syntax methodSPSS outputResults and interpretationGrouped frequency distributionsGrouping scores into class intervalsComputing a frequency distribution of grouped scoresSPSS methodSPSS Windows methodSPSS syntax methodSPSS outputPercentiles and percentile ranksPercentilesComputation of percentiles (finding the score below which a specified percentage of scores will fall)SPSS syntax methodData entry formatSPSS syntax methodSPSS outputAnother exampleData entry formatSPSS syntax methodSPSS outputPercentile rankComputation of percentile ranks (finding the percentage of scores that fall below a given score)Data entry formatSPSS syntax methodSPSS outputAnother exampleData Entry FormatSPSS Syntax MethodSPSS OutputGraphingGraphing frequency distributionsBar graphAn exampleData entry formatSPSS Windows methodSPSS syntax methodSPSS bar graph outputHistogramAn exampleSPSS Windows methodSPSS syntax methodSPSS histogram outputFrequency polygonAn exampleSPSS Windows methodSPSS syntax methodSPSS frequency polygon outputCumulative percentage curveAn exampleSPSS Windows methodSPSS syntax methodSPSS Cumulative percentage OutputMeasures of central tendencyWhy is central tendency important?Measures of central tendencyThe arithmetic meanHow to calculate the arithmetic meanSPSS Window methodSPSS syntax methodSPSS outputHow to calculate the mean from a grouped frequency distributionAn exampleCalculating the mean from grouped frequency distribution using SPSSData entry formatSPSS syntax methodSPSS outputThe overall meanAn exampleHow to calculate the overall meanusing SPSSData entry formatSPSS syntax methodSPSS outputProperties of the meanThe medianCalculating the median for ungrouped scoresCalculating the median for grouped scoresProperties of the medianThe modeSPSS windows methodSPSS syntax methodSPSS histogram outputThe mode for grouped scoresComparison of the mean, median and modeMeasures of central tendency: symmetry and skewnessMeasures of variability/dispersionWhat is variability?RangeStandard deviationCalculating the standard deviation using the deviation scores methodCalculating the standard deviation using the raw scores methodVarianceUsing SPSS to calculate the range, the standard deviation, and the varianceSPSS Windows methodSPSS syntax methodSPSS outputThe normal distribution and standard scoresThe normal distributionAreas contained under the standard normal distributionStandard scores (z scores) and the normal curveCalculating the percentile rank with z scoresSPSS Windows methodSPSS syntax methodSPSS data file containing the first 0computed z scoresCalculating the percentage of scores that fall betweentwo known scoresCalculating the percentile point with z scoresSPSS Windows methodSPSS syntax methodTable showing the 90th percentile for the setof 0 exam scoresCalculating the scores that bound a specified area of thedistributionSPSS Windows methodSPSS syntax methodTable showing the approximate lower and upper bound scores that bound the middle 70% of the statistics exam\'s distributionUsing z scores to compare performance between different distributionsCorrelationThe concept of correlationLinear and non-linear relationshipsCharacteristics of correlationMagnitude (strength) of relationshipsDirection of relationshipsCorrelation coefficient and z scoresScatter plot (SPSS Windows method)Scatter plot (SPSS syntax method)Scatter plotConverting raw scores into z scores (SPSS Windows method)Converting raw scores into z scores (SPSS syntax method)SPSS data file containing the pairs of computed z scoresPearson r and the linear correlation coefficientExample of the Pearson r calculationSPSS Windows methodSPSS syntax methodThe calculated Pearson rSome issues with correlationCan correlation show causality?Spurious correlationLinear RegressionWhat is linear regression? Linear regression and imperfect relationshipsScatter plot and the line of best fitSPSS Windows method (scatter plot and line of best fit)SPSS syntax method (scatter plot)Scatter plot with line of best fitLeast-squares regression (line of best fit): Predicting Y from XHow to construct the least-squares regression line: Predicting Y from XSPSS Windows method (constructing the least-squares regression line equation)SPSS syntax method (constructing the least-squares regression line equation)SPSS outputResults and interpretationINFERENTIAL STATISTICSStatistical inference and probabilityIntroduction to inferential statisticsProbabilityThe classical approach to probabilityThe empirical approach to probabilityExpressing probability valuesComputing probability: The addition rule and the multiplication ruleThe addition ruleThe multiplication ruleUsing the multiplication and addition rules togetherComputing probability for continuous variablesSamplingSimple random samplingStratified proportionate random samplingCluster samplingNon-random sampling techniques: Systematic sampling
 quota samplingSampling with or without replacementConfidence interval and confidence levelHow to calculate the confidence intervalSPSS Windows methodSPSS syntax methodIntroduction to hypothesis testingIntroduction to hypothesis testing .Types of hypothesesResearch/alternative hypothesisNull hypothesisHypotheses: Non-directional or directionalTesting hypothesesLevel of significanceTwo-tailed and one-tailed test of significanceType I and Type II errorsHypothesis testing: t test for independent and correlated groupsIntroduction to the t testIndependent t testSPSS Windows method: Independent t testSPSS syntax methodSPSS outputResults and interpretationDependent/correlated t testSPSS Windows Method: Dependent t testSPSS syntax methodSPSS outputResults and interpretationHypothesis testing: One-way analysis of varianceOne-way analysis of variance (ANOVA)An exampleScheffe post hoc testSPSS Windows method: One-way ANOVASPSS syntax method SPSS outputResults and interpretationPost hoc comparisonsHypothesis testing: Chi-square testNon-parametric testsChi-square ( (2)) testChi-square goodness-of-fit testSPSS Windows methodSPSS syntax methodSPSS outputResults and interpretationChi-square ( (2)) test of independence between two variablesSPSS Windows methodSPSS syntax methodSPSS outputResults and interpretationAppendicesBibliographyIndex