exam 2

• 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