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SYG 4300-02Social Research MethodsFinal Review Guide: This is a broad list of concepts relevant to the final exam. I encourage you to know concepts, examples, calculations and interpretations. Sample Elements• The individual units, often individual persons, that comprise a sampleSampling Frame• List of all the sampling units from which the sample is drawn• Ex: telephone directories, tax records, driver’s license records. Sampling Error• Sampling error is the deviation of the selected sample from the true characteristics, traits, behaviors, qualities or figures of the entire population.• Sampling process error occurs because researchers draw different subjects from the same population but still, the subjects have individual differences.• Ways to eliminate:o This solution is to eliminate the concept of sample, and to test the entire population.Representativeness• Subset of a statistical population that accurately reflects the members of the entire population• Unbiased indication of what population is likeProbability vs. Non-probability Sampling Methods• Non-probability sampling o Probability of being chosen is unknowno To satisfy concerns about the sample’s representativeness, the researcher must explicitly explain how the sample represents the population from which it was drawn. o Cheaper but unable to generalizeo Potential for biaso Convenience Sample (ease of access): sample is selected from elements of a population that are easily accessible• Probability samplingo Methods for drawing a sample in which the probability of selecting population elements is known. The researcher uses random sampling so that the representativeness of the sample characteristics to the (known) population characteristics can be statistically calculated. o Random Sample: each subject has a known probability of being selectedo Allows application of statistical sampling theory to result to: Generalize Test hypothesis Ensure representativeness and precisionSystematic Random Sample (probability sample) • Create a sampling frame, calculate the sampling interval 1/k, choose a random starting place, then take every 1/k case. • For example, suppose you want to sample 8 houses from a street of 120 houseso 120/8= 15, so every 15th house is chosen after a random starting point between 1 and 15. o If the random starting point is 11, then the houses selected are 11, 26, 41, 56, 71, 86, 101, and 116. • Advantages:o Spreads the sample more evenly over the populationo Easier to conduct than a simple random sample• Disadvantages: o The system may interact with some hidden pattern in the population, e.g. every third house along the street might always be the middle one of a terrace of three. Stratified Random Sample (probability sample)• Create a sampling frame for each of several categories of cases, draw a random sample from each category, then combine the several samples. • In the first stage, elements are sorted into separate groups (called “strata”) according to the selected group characteristics.• In the second stage, elements are randomly sampled from within strata. • Usually use when a stratum of interest is a small percentage of a population and random processes could miss the stratum by chance • Ex: you have a population that is 51% female and 49% male.o You draw 2 random samples, one of all females and one of all males (ex: for a sample of 1,000, draw 510 randomly from a list of males and 490 from a list of females) Final sample will have a 51 to 49 percent sex ratio• Ex: draw a sample of 200 from 20,000 college students and get information that 2% or 400 are divorced women with children under the age of 5.o There would be 4 such students in a representative sampleo In stratified random sample, you obtain a list of the 400 such students and randomly select 4 from it. • Advantages:o Captures key population characteristics in the sampleo Works well for populations with a variety of attributesCluster Sample (probability sample) • A random sampling plan in which the population is subdivided into groups called clusters so that there is small variability within clusters and large variability between clusters.• Then the required information is collected from a simple random sample of the elements within each selected group.• Advantages:o Cheaper• Disadvantages:o Higher sampling errorAvailability Sample (Convenience sample) (nonprobability sample) • A nonprobability sample in which elements are drawn based on their availability to the researcher. • The person-on-the-street interview conducted by television programs is an example • Ex: a newspaper that asks readers to clip a questionnaire from the paper and mail it in. o Not everyone reads the newspaper, has an interest in the topic, or will take time to cut it out and mail it. Quota Sample (nonprobability sample) • Quota sampling is a non-probability sampling technique wherein the assembled sample has the same proportions of individuals as the entire population with respect to known characteristics, traits or focused phenomenon.o The first step in non-probability quota sampling is you first identify relevant categories among the population you are sampling to capture diversity among units (e.g., male and female; under age 30, ages 30-60, 60 and over, etc.)o Next, you determine how many cases to get for each category, this is your “quota” o Then, you fix a number of cases in various categories of the sample at the start. o The final step ensures that the sample is representative of the entire population. It also allows the researcher to study traits and characteristics that are noted for each subgroup.• Ex: you interview the first 5 males under 30 you encounter, even if all 5 had just walked out of the campaign headquarters of a political candidate.o Nothing prevents you from choosing people who “act friendly” or who want to be interviewed• Ex: George Gallup successfully predicted the outcomes of the 1936, 1940, and 1944 U.S. presidential elections. o In 1948, selected the wrong candidateo Major reason was that the quota categories did not accurately represent all geographical areas andall people who actually cast a vote. • Advantages:o Allows the researcher to sample a subgroup of great interest to the studyo Allows researcher to observe relationships between subgroups • Disadvantageso May not always be representative of the populationo Traits may be

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