MKTG 334 1st Edition Exam # 3 Study Guide SamplingDefine population.Any complete group whose members share some common set of characteristics Why do researchers use same insteada of conducting a census of an entire population?More practical to use because it is usually less expensive and faster than conducting a census, when testing requires the destruction of the items being tested, samples can give accurate and reliable resultsWhat is a technical term that refers to statistical fluctuations that occur because of chance variation in the elements selected for the sample?Random sampling errorKnow examples of non probability sampling techniques. Quota sampling, convenience sampling, snowball samplingDefine judgment sampling.A sampling technique in which an experienced individual selects the sample based on his or her judgment about some appropriate characteristic required of the sample member What is an example of quota sampling?If an interviewer is instructed to sample 100 freshmen, 100 sophomores, 100 juniors, and 100 seniors in a study of college students attitudes toward collegiate athletic fundingDefine snowball sampling.A sampling procedure that builds a sample through referrals of other population membersWhen is simple random sampling used?When a researcher wants a sampling procedure that ensures that wach element in the population has anequal chance of being included in the sampleDefine systematic sampling Randomly selecting a starting point on a list and then selecting every th valueDefine proportional stratified sampling Type of sampling which units are drawn from each stratum proportionate to the population size of that stratumWhat type of sampling involves using a combination of two or more probability sampling techniques ?Multistage area samplingWhat sampling is useful in locating members of rare populations ?SnowballWhat sampling techniques are low cost/ high costLow: clusterHigh: simple random, stratified, multistageWhat does appropriate sample design depend on?Degree of accuracy, resources, timeBasic Data AnalysisDefine descriptive analysis The elementary transformation of raw data in a way that decribes the basic characteristics such as central tendency, distribution, variabilityDefine tabulationThe orderly arrangement of data in a table or other summary format showing the number of responses to each responses categoryDefine cross-tabulationAddresses research questions involving relationships among multiple less than interval variable, results in a combined and another variable in columnsDefine data transformationProcess of changing the data from their original form to a format for performing a data analysis addressing research objective Define median splitDividing a data set into two categories by placing respondents below the median in one category and respondents above the median in another, the approach is best applied only when the data do indeed exhibit bimodal characteristics Define interpretationThe process of drawing inferences from the analysis resultsUnivariate analysis Define univariate statistical analysis and bivariate statistical analysisUnivariate- tests of hypotheses involving only one variable, testing of statistical significanceBivariate- tests of hypotheses involving two variablesDefine significant level and p-valueSignificance level- a critical probability associated with a statistical hypothesis test that indicates how likely an inference supporting a difference between an observed value and some statistical expectation istruep-value- probability value or the observed or computed significant level, higher p vales equal more support for an hypothesis Define chi-square test and goodness of fitChi-square is tests for statistical significance, appropriate for testing hypotheses about frequencies arranged in a frequency tableGoodness of fit – general term representing how well some computed table or matrix of values matrix some population or predetermined table or matrix of the same