IR 211 1st EditionExam # 2 Study Guide- External validity o The process of testing the validity of a measure, such as an index or scale, by examining its relationship to other, presumed indicators of the same variable Ex: if the index really measures prejudice, it should correlate with other indicators of prejudiceo Key problem is to have to worry about stimulus; when you try to generalize from what happened to the real world is a challenge – external invalidityo The Solomon four group design – addresses the problem of testing interaction with the stimulus; involves 4 groups of randomly assigned subjects; permits 4 meaningful comparisons- Internal validityo Experimentation is a method that works best when the tradeoff between external validity and internalvalidity is managed effectively o Internal invalidity occurs when experimental results may not accurately reflect what has gone on in the experiment itself; threat is present whenever anything other than the experimental stimulus can affect the dependent variableo 12 sources of internal invalidity history – historical events may occur during the course of the experiment that may confound the results  maturation – of the participants [growing older – long term, growing tired – short term] testing – process of testing and re-testing may influence ppls behavior instrumentation – if different questionnaires, for ex, are use in pre and post testing, how can it be certain they are each measuring exactly the same thing? Issue of conceptualization and operationalization statistical regression – danger that changes occurring by virtue of the participants starting out in extreme positions will be attributed erroneously to the effects of the experimental stimulus [ie extremely tall people are likely to have children shorter than them] selection biases – groups need to be comparable at the start of an experiment experimental mortality – subjects may drop out of an experiment before it is completed causal time order – ambiguity about the time order of the experimental stimulus and the DV [may be the DV caused the changes in stimulus instead of vice versa] diffusion or imitation of treatments – experimental group might pass on elements of the experiment to the control group and control group is “contaminated” compensation – subjects in the control group are often deprived of something to be of value; they may be treated differently out of guilt – no longer a genuine control group compensatory rivalry – subjects deprived of experimental stimulus may try to compensate by working harder demoralization – feelings of deprivation within the control group may result in their giving up- Survey validityo If you ask people about something they know nothing about, you will get skewed answers because people don’t want to look ignoranto Bias and wording is a menace with surveys; need to seek neutral wordingo Changes in what is acceptable socially can change very fast- Naturalismo Naturalism is the most time honored approach to field research – based on the assumption that an objective social reality exists and can be observed/reported accurately Naturalism – belief in objective reality- Ex: UN can be observed and understood through our experiences Critics say that things that are really important are not the parts that are objective Naturalists believe in nomothetic explanations – the experiences of others will be clear to me and vice and versao Reasons for naturalistic observation: To describe nature – leave variable uncontrolled and are of limited use for testing causal hypotheses, but descriptions can provide evidence that support or discredit hypotheses To generate and test hypotheses – observations can lead to hypotheses to assess behavior – changes in behavior can be measured and evaluated even if the starting point is unknown Because other methods are impractical – ethical considerations limit some experiments; experiments can not answer all questions; experiments may lead to biased responses- Quantitative Datao Numerical representation of hypotheses, of our findings, and our arguments; mathematical statements about datao Not in opposition to qualitative, but rather complementary too Often makes observation more explicit, easier to aggregate, compare and summarize datao Tends to be less rich in meaning than qualitative analysis but more straightforward; more precise information- Bivariate Analysiso The analysis of two variables simultaneously; purpose is descriptive; adds the element of determining the relationship between variables themselves – focus on the variables and their empirical relationships Ex: church attended recorded by men and women – shows that women attended church more often than men; same table also suggests that the variable gender has an effect on the variablechurch attendance [no longer talking about men and women as separate subgroups but as gender as a variable]o Has been important in generating results and moving social science forward in the connections we seeand in the things that don’t work out Ex: population density, Malthusian [more density of people = greater conflict - interstate] – didn’t work; what does seem to have some connection is population density and civil warfare- Stratified sampling o Trying to get more representativeness by decreasing probably sampling error; group units into homogenous collections before sampling out of themo A method for obtaining a greater degree of representativeness by decreasing the probable sampling error [sampling error is reduced by increasing the sample size and by having a homogenous population]o Rather than selecting a sample from the total population at large, the researcher ensures that appropriate numbers of elements are drawn from homogenous subsets of that population Ex: a stratified sample of university students – you would first organize your population by college class and draw appropriate numbers of freshman, sophomore, juniors, and seniorso Ultimate function is to organize population into homogenous subsets - Test Variable o Also called the control variableo The variable that is held constant in an attempt to clarify further the relationship between two other variables Ex: relationship discovered between education and prejudice – could hold the variable gender constant by testing the relationship between