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| Samples in which the elements to be selected are drawn on the bsaes of probability. Each element in a population has a certain probability of being selected as part of the sample. |
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| A sample obtained by stratifying the sampling frame and then selecting a fixed number of items from each of the strata by means of a simple random sampling technique. (Same number across the board) you would divide this large pool of subjects into several groups (strata) and then randomly select subjects from within each group. The number of subjects selected from each group is fixed by design. |
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| Qualitative - Nominal and ordinal (ordered ranking) |
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Quantitative. Measurement. Ex: age, distance, time.
Definitive or continuous - definitive - you can count it. |
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| A sample design in which the elements of the sampling frame are treated equally and there is NO subdividing or partitioning of the frame. |
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A sample obtained by stratifying the sampling frame and then selecting some or all of the items from some, not all, of the strata.
More time effective. |
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| Consists of results collected from those elements of the population that chose to contribute to the needed info on their own initiative. |
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Selected in such a way that every element in the population or sampling frame has an equal probability of being chosen.
Ex: each employee is assigned a number and a computer is used to randomly select 35. |
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| Samples that are selected on the basis of being judged "typical". The person selecting the sample chooses tiems that he or she thinks are representative of the population. The validity of the results from a judgement sample reflects the soundness of the collecter's judgement. |
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| Convenience sample/ grab sample |
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Definition
| Occurs when items are chose arbitrarily and in an unstructured manner from a population. |
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| A sample design in which elements of the sampling frame are subdivided and the sample is chosen in more than 1 stage. Often start by dividing a very large population into subpopulations on the basis of some characteristic. |
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| EXAMPLE: A TV researcher wants a quick sample of opinions about a political announcement. They stop what seems like a reasonable cross-section of people in the street to get their views. |
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Definition
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| Types of proabibility sampling |
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Definition
Single stage Sampling:
-Simple random sample
-systematic sample
Multistage sampling:
-Stratified random sample
-proportional sample
-cluster sample |
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| EXAMPLE: Suppose that the Department of Agriculture wishes to investigate the use of pesticides by farmers in England. A cluster sample could be taken by identifying the different counties in England as clusters. A sample of these counties (clusters) would then be chosen at random, so all farmers in those counties selected would be included in the sample. It can be seen here then that it is easier to visit several farmers in the same county than it is to travel to each farm in a random sample to observe the use of pesticides. |
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Definition
| Cluster sampling (form of multistage sampling of probability) |
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| EXAMPLE: Suppose a farmer wishes to work out the average milk yield of each cow type in his herd which consists of Ayrshire, Friesian, Galloway and Jersey cows. He could divide up his herd into the four sub-groups and take samples from these. |
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Definition
| Stratified sampling - a form of multistage sampling of probability. |
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| EXAMPLE: a group of 25 employees chosen out of a hat from a company of 250 employees. In this case, the population is all 250 employees, and the sample is random because each employee has an equal chance of being chosen. |
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Definition
| Simple random sample - single stage probability sample |
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| EXAMPLE: Suppose a supermarket wants to study buying habits of their customers, then using systematic sampling they can choose every 10th or 15th customer entering the supermarket and conduct the study on this sample. |
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Definition
| systematic sample method - single step probability sample. |
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