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.
Simplerandom 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.
Stratifiedrandom 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.
Samplingerror 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.