Data Collection Sampling. Target Population The group of people to whom the researcher wishes to...
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Transcript of Data Collection Sampling. Target Population The group of people to whom the researcher wishes to...
Target Population
The group of people to whom the researcher wishes to generalize the results of the study
Accessible Population
-The smaller portion of the target population to whom the researcher actually has access
Sampling
the process of selecting a portion of the target population (sample) in such a way that the individuals chosen represent, as nearly as possible, the characteristics of the target population.
Sampling Bias
-An overrepresentation or underrepresentation of some characteristic in the sample relative to the target population
Unconscious
Conscious
The extent to which bias is a concern is a function of the homogeneity or heterogeneity of the target population.
When a variation (relevant to the research question) occurs in a population, then it must occur in the sample
Sampling error
-the fluctuation of a statistic from one sample to another drawn from the same population. (Can be estimated with probability sampling) Note: the larger the sample, the less sampling error.
Probability Sampling
-Sampling procedures use some form of randomization to select samples from the population.
Convenience Sampling(Accidental Sampling) Involves the use of the most
convenient and readily available subjects for the sample.– Man on the street interviews– Teacher uses students– Volunteers
Convenience/accidental sampling
Problem: Sample bias because of “self selection”--available subjects may be highly atypical of the population with regard to critical variables.
SNOWBALL SAMPLING”
Variation of above, used when subjects are hard to find. One subject recommends another. Even more prone to bias.
Convenience sampling is the most widely used yet weakest form of sampling. There is no way to evaluate all of the biases that may be operating.
QUOTA SAMPLING
Researcher uses some knowledge of the population to build some representativeness into the sampling plan
divides population into different strata and samples from each of them
USUALLY BETTER THAN JUST CONVENIENCE
THE BASIS OF THE CHARACTERISTICS CHOSEN SHOULD REFLECT IMPORTANT DIFFERENCES IN THE DEPENDENT VARIABLE– age– gender– ethnicity– socioeconomic status– education– medical diagnosis– occupation
Quota Sampling
Problem: you cant always determine which characteristics in the sample are going to be reflected in the dependent variable
PURPOSIVE SAMPLING“Judgmental Sampling” PROCEEDS ON THE BELIEF THAT
THE RESEARCHER KNOWS ENOUGH ABOUT THE POPULATION AND ITS ELEMENT TO HANDPICK THE SAMPLE– selects “typical” persons– selects widest variety
Purposive or Judgemental Sampling Assumption: judgemental errors will tend to balance
out.
Risk of conscious bias greatly multiplied Should be avoided if the population is
heterogeneous.
PROBABILITY SAMPLING
SIMPLE RANDOM STRATIFIED RANDOM CLUSTER
The probability of any member of the target population being included in the sample can be calculated.
SYSTEMATIC SAMPLING(Can be either probability or non probability)
SIMPLE RANDOM SAMPLING
identify population
establish sampling frame
number elements in sampling frame consecutively
randomly select from list
Random sampling does not guarantee representativeness, it does guarantee that difference between the sample and the population are purely a function of chance.
STRATIFIED RANDOM SAMPLE
The population is divided into two or more strata by relevant characteristics and subjects are randomly chosen from these strata
Slightly better than simple random, especially if the sample is not very large.
CLUSTER SAMPLING
Multistage sampling process Used when target population is very
large
Results in more sampling error
Statistical analysis more complicated
SYSTEMATIC SAMPLING
Selection of every Kth case from a list of possible subjects.
( K represents any number)
SAMPLE SIZE
N Determined by: COHEN’S POWER ANALYSIS
Determine “effect size of treatment”
Use in power analysis formula
Achieves the least measurement error