exam 2

Cards (88)

  • what is the gold standard of sampling?
    random sampling
  • why is random sampling often not possible for the vast majority of research?
    not possible due to fixed conditions, not practical, not always desirable
  • probability sample: likelihood that any individual in the population being selected can be specified, most common type is simple random sampling
  • non-probability sample: likelihood that any individual in the population being selected can not be specified
  • when are random samples most desirable?
    when the researcher wants to accurately describe a population
  • probability samples, including random samples, are virtually never used in psychological research. Psych research does not describe how a population behaves, it tests the relationship between psychological variables
  • A representative sample, as opposed to a random sample, is always desirable
  • sampling error: differences arise between sample results and the parallel results when the entires population is measured
  • the sampling error can be estimated with the error of estimation, margin of error and confidence intervals
  • what factors influence the margin of error in a probability sample?
    sample size, population size, variance of the data
  • winning 45% of a vote with a 3% margin of error means 95% of the time, between 42% and 48% of the vote is won
  • simple random sample: every member of population has equal probability of being selected. in small samples, can be done mechanically. in large samples, computerized randomization is used
  • systematic sampling: select some starting point and the select every nth element in the population (e.g. "every fourth person"
  • stratified random sampling: divide population into strata (gender, ethnicity, etc.), select randomly from each stratum. political polls
  • which methods require a sampling frame (where all members of pop. are accessible)?
    simple random sampling and stratified random sampling
  • cluster of multi-stage sampling: for very large populations where everyone cannot be accessed
  • steps to increase participation?
    pester, incentives, simplify survey, advance notice, follow-up
  • misgeneralization: generalizing to a population not represented in sample
  • nonprobability sample: any sample in which little or no attempt is made to get a representative cross section of the population. convenience sampling, quota samples, purposive samples
  • convenience sample: most common type in psych research. usually college students, often adequate, use different samples for comparison
  • quota samples: convenience sample where certain types of participants are obtained in particular proportions (e.g. ethnic breakdowns)
  • purposive sampling: researchers use past research findings or judgement to decide who to include in sample (election sampling)
  • participant number dilemma: a large number of subjects will provide more valid results, but we must weight the cost/benefit of acquiring more subjects
  • type 1 error: we say there is a difference between groups or a variable relation, but there is not
  • type 2 error: we say there is no difference of variable relation, but there is
  • p-value: significance
  • power: probability of finding a significance between groups/variable relation
  • a higher alpha gives more power. usually 0.5 higher alpha means a higher chance of a type 1 error
  • one-tailed tests are more powerful than two-tailed tests. directional hypotheses more valuable
  • a larger effect size gives more power
  • a larger sample gives more power than smaller samples. resources limit this
  • correlation: relationship between two or more variables
  • how do we determine whether one variable is affected by another?
    we see if the scores of these variables covary (vary or change together)
  • bivariate correlation: simple correlation between two variables
  • correlations are designed by the letter r, which ranges between -1 to +1
  • a correlation is also known as the person product-moment or the person r
  • the pearson r is predicated on the assumption that the two variables involved are approximately normally distributed
  • when variables are not normally distributed, the Spearman correlation is more appropriate
  • perfect correlations are almost never found in the social sciences, primarily a mathematical or theoretical construct
  • correlations only measure linear relationships