Class 12

Cards (55)

  • Element or unit: a single case in the population.
  • Population: all cases that a researcher is interested in.
  • Sampling frame: the list of elements that the sample will be selected from.
  • Sample: the elements (subset of a population) selected for investigation.
  • Representative sample: a sample that contains the same essential characteristics as the population.
  • Probability sample: a sample selected using a random process so that each element in the population has a known likelihood of being selected.
  • Non-probability sample: a sample selected using a non-random method.
  • Sampling error: estimation the error that occurs because of differences between the characteristics of the sample and those of the population.
  • Non-response: when an element selected for the sample does not supply the required data.
  • 40PPAP stands for "Raise Your Hand if You Know What This Is".
  • A factor related to 40PPAP is being in the age range of 20-30.
  • Another factor related to 40PPAP is being a regular Facebook User.
  • Being a Blogger is a factor related to 40PPAP.
  • A third factor related to 40PPAP is being a regular Twitter User.
  • Having kids is a factor related to 40PPAP.
  • A fourth factor related to 40PPAP is owning a Smartphone.
  • Census: data that comes from an attempt to collect information from all elements in the population.
  • Sampling: the selection of a subset of a population for research.
  • Probability sampling: uses random selection methods, associated with quantitative methods.
  • Non-probability sampling: does not use random selection methods, associated with qualitative research.
  • Simple random sample: where each element has the same probability of being selected & each combination of elements has the same probability of being selected.
  • Systematic sample: for every ith case in the sampling frame is selected.
  • Stratified random sample: this type of sampling ensures that subgroups in the population are proportionally represented in the sample.
  • Sample size is often dictated by financial concerns.
  • Sampling error is inevitable, but probability samples with sufficient sample sizes minimize the amount of sampling error, as measured by a statistic called the standard error of the mean.
  • Snowball Sampling involves the researcher making contact with some individuals, who in turn provide contacts for other participants.
  • Even when a sample is selected using probability sampling, any findings can be generalized only to the population from which the sample was taken.
  • The greater the heterogeneity of the population on the characteristics of interest, the larger the sample size should be.
  • Structured Observation Sampling often involves no sampling frame, for example, a list of all people who were admitted to the emergency room at a particular hospital.
  • Behavior Sampling involves observing every fifth interaction between students and librarians at a particular reference desk.
  • Sampling error and sampling related error arise from activities or events related to the sampling process, such as non-response, inadequate sampling frame, etc.
  • Each size increase cuts the sampling error by 1/2, then 1/3, then 1/4, and then 1/5 respectively.
  • The absolute size of the sample matters, not the proportion of the population that it comprises.
  • Place Sampling involves observing in specific places such as dining halls, pubs, classrooms, etc.
  • The biggest change occurs between 100 and 400.
  • About 95 per cent of all sample means lie within 1.96 standard errors of the mean.
  • Common sample sizes are 100, 400, 900, 1600, 2500.
  • Time Sampling involves observing at random times throughout the day.
  • As sample size increases, sampling error tends to decrease.
  • The response rate is the percentage of the sample that participates in the study.