Table 1.1:Defining the components of the scientific method.
Table 2.1:Categories of social science variables.
Table 2.2:The four levels at which scientific variables are measured.
Table 2.3:Features of most scientific reports.
Table 3.1:Respect scores for teacher.
Table 3.2:Types of statements scientists rarely and frequently make.
Table 3.3:Comparison of three different approaches to teaching artistic expression.
Table 4.1:Results of a silly hypothetical study.
Table 4.2:A diagram representing the entire range of correlation coefficients.
Table 4.3:Correlation between wealth and male fertility.
Table 4.4:Bivariate and partial correlation coefficients linking religiosity and delinquency.
Table 5.1:Excerpts from research report on the lunar cycle and suicide.
Table 6.1:Average age of death according to handedness.
Table 6.2:Correlation matrix.
Table 6.3:Factor analysis of focal concerns characteristics.
Table 7.1:Conversion of sample size into percentage confidence intervals.
Table 8.1:Return rates in some contemporary mail surveys.
Table 8.2:Average response rates in three different types of surveys.
Table 8.3:Comparisons of self-reported drinking patterns.
Table 8.4:Topics that cause people to feel uneasy in research interviews.
Table 8.5:Differences between responses after the bogus pipeline and after a face-to-face interview.
Table 9.1:Examples of studies based on scenario-type questions.
Table 9.2:Examples of widely used multi-item scales in the social and behavioral sciences.
Table 10.1:Examples of studies based on participant observations.
Table 10.2:Examples of studies based on ethnographic observations.
Table 10.3:Examples of case studies in the social and behavioral sciences.
Table 10.4:Examples of studies based on focus group methodology.
Table 10.5a:Examples of studies based on prehistoric archeological data.
Table 10.5b:Examples of studies based on historic archeological data.
Table 10.6:Analysis programs primarily designed for qualitative data.
Table 10.7:Examples of studies based on laboratory and clinical data.
Table 10.8:Examples of laboratory studies that infer behavior.
Table 10.9:Examples of naturalistic field observational studies.
Table 10.10:Examples of studies based on manipulative field research
Table 10.11:Naturalistic animal observations.
Table 10.12:Examples of research based on content analysis.
Table 10.13:The main types of qualitative direct observational data.
Table 10.14:The main types of quantitative direct observational data.
Table 11.1:Examples of studies based on analyses of contemporary archival data.
Table 11.2:Examples of agencies with massive data sets on the Internet.
Table 11.3:Examples of studies based on analyses of historic archival data.
Table 11.4:Cross-cultural studies based on data available in ethnographic atlases.
Table 11.5:Examples of topics addressed by meta-analyses.
Table 11.6a:Relationships between social status and criminal and antisocial behavior.
Table 11.6b:Relationships between parental social status and criminal and antisocial behavior.
Table 12.1:Estimated number of arrests for crimes by sex and age.
Table 12.2:Items and factor loadings for a self-report measure of psychopathy.
Table 13.1:Examples of animal models developed to understand human behavior.
Table 15.1:Comparisons of quasi-experiments and actual controlled experiments.
Table 17.1:Examples of evaluation research applied to primary prevention programs.
Table 17.2:Examples of evaluation research applied to secondary prevention programs.
Table 17.3:Examples of evaluation research involving treatment programs.
Table 17.4:Examples of evaluation research applied to improvement-oriented programs.
Table App. 1:Mock-up of the first three pages of a typical research report.
Figure 3.1:A frequency distribution curve based on hypothetical data.
Figure 3.2:A bimodal distribution curve based on hypothetical data.
Figure 3.3:Distribution in annual income for U.S. workers, 1982.
Figure 3.4:Duration of marriages that ended in divorce in the United States in 1979.
Figure 3.5:Frequency distribution curve based on hypothetical data.
Figure 3.6:A frequency distribution curve based on hypothetical data.
Figure 3.7a:Two overlapping normal curves not considered different to a statistically significant degree according to a t-test.
Figure 3.7b:Two overlapping normal curves considered different to a statistically significant degree according to a t-test.
Figure 4.1:Scattergram based on five hypothetical observations between shoe size and age.
Figure 4.2:Scattergram based on five hypothetical observations of scores on Variables M and N.
Figure 4.3:Scattergram based on forty-seven hypothetical observations of scores on Variables Y and X.
Figure 4.4:Scattergram of the relationship between Variables Y and X.
Figure 4.5:Scattergram of the relationship between Variables 1 and 2.
Figure 4.6:Scattergram representing the relationship between Variables M and N.
Figure 4.7:Samples of the most common shapes of curvilinear correlational patterns.
Figure 4.8:Scattergram of the relationship between Variables A and B.
Figure 4.9:Relationship between property crime rates and dispersions in income.
Figure 6.1:Mean number of aggressive responses per minute.
Figure 6.2:Trends in homicide rates for various large European cities.
Figure 8.1:Example of a flash card.
Figure 11.1:Degree of income inequality and mortality rates.
Figure 12.1:Example NCVS victimization questions.
Figure 12.2:Comparisons of new NCVS and old NCS screener questions.
Figure 12.3:Increased reporting due to redesigned interviewing procedures.
Figure 13.1:A diagrammatic scheme of two competing theories.
Figure 13.2:Idealized interrelationship between theories, hypotheses, empirical observations, and generalizations.
Figure 13.3:Proposed model for how drug use by peers and self interrelate.
Figure 13.4:Path analysis model of factors influencing occupational status.
Figure 13.5:Photograph of MAO knock-out mice.
Figure 13.6:Concepts of a universe as a whole, a local universe, and a sample.
Figure 13.7:Researcher’s options concerning null hypothesis and possible outcome.
Figure 14.1:A classical experimental design.
Figure 14.2:A study to reduce the number of women who smoked during pregnancy.
Figure 14.3:Basic after-only experimental design.
Figure 14.4:Before-after no control group experimental design.
Figure 14.5:Before-after no control group experimental design to assess the effects of Ritalin.
Figure 14.6:Before-after no control group experiment on increasing seat-belt usage.
Figure 14.7:A cross-over experimental design to determine if college students learn as well watching lectures in person as on video.
Figure 14.8:A basic Solomon four-group experimental design.
Figure 14.9:A two-by-two factorial experimental design.
Figure 15.1:Per capita sales of cigarettes in Wisconsin, 1950–1988.
Figure 15.2:Deaths during the twelve weeks prior to and following decedent’s birthday.
Figure 15.3:Murders during the four weeks preceding and six weeks following executions in London.
Box 12.1:Using the UCR and NIBRS to test contending hypotheses.
Box 12.2:Using the UCR and NCVS to test alternative hypotheses.