LESSON 3 Flashcards
Types of POPULATION
- Target Population
- Accessible Population
The group defined by the researcher’s specific interests. Individuals in a _______ typically share one characteristic.
Target Population
The part of the target population that can be accessed by the researchers.
Accessible Population
The entire set of individuals who have the characteristics required by the researcher.
The Target Population ( The Population)
A portion of the target population consisting of individuals who are accessible to be recruited as participants in the study.
The Accessible Population
The individuals who are selected to participate in the research study.
The Sample
HOW DO WE MAKE SURE THAT THE STATISTICS AND INFERENCES CAN BE GENERALIZED TO THE POPULATION?
The _______ of a sample refers to the extent to which the charactreristics of the sample accurately reflect the characteristics of the population.
Representatives
A _______ is a sample with the same characteristics as the population.
Representative Sample
A ______ is a sample with different characteristics from those of the population.
Biased Sample
_______ or “sampling bias” occurs when participants or subjects are selected in a manner that increases the probability of obtaining a biased sample.
Selection Bias
The process of selecting individuals for a study is called _______.
Sampling
Researchers have developed a variety of different _______ (also calles “sampling techniques” or “sampling procedures”)
Sampling Methods
Two types of Sampling Technique
- Probability Sampling (all has equal chances)
- Non-Probability Sampling (not all has the chance to be selected)
In _______, the entire population is known, each individual in the population has a specifiable probability of selection, and sampling occurs by a random process based on the probabilities.
Probability Sampling
In _______, the population is not completely known, individual probabilities cannot be known, and the sampling method is based on factors such as commonsense or ease, with an effort to maintain representativeness and avoid bias.
Non-Probability Sampling
Probability Sampling Techniques
- Simple Random Sampling
- Systematic Sampling
- Stratified Random Sampling
- Proportionate Stratified Random Sampling
- Cluster Sampling
The basic requirement for random sampling is that each individual in the population has an equal chance of being selected. Equality means that no individual is more likely to be chosen than another. A second requirement that is sometimes added is that each selection is independent of the others. Independence means that the choice of one individual does not influence or bias the probability of choosing another individual.
Simple Random Sampling
Process of Simple Random Sampling :
- Clearly define the population from which you want to select a sample.
- List all the members of the population.
- Use a random process to select individuals from the list.
2 Principal Methods of Random Sampling
- Sampling with replacement ( the chance is constant )
- Sampling without replacement ( others can have their chance )
_______ is a type of probability sampling that is very similar to simple random sampling. ______- begins by listing all the individuals in the population, then randomly picking a starting point on the list. The sample is then obtained by moving down the list, selecting every nth name.
Systematic Sampling
We first identify the specific subgroups (or strata) to be included in the sample. Then we select equal-sized random samples from each of the pre-identified subgroups, using the same steps as in simple random sampling. Finally, we combine the subgroup samples into one overall sample.
Stratified Random Sampling
As with a stratified sample, we begin by identifying a set of subgroups or segments in the population. Next, we determine what proportion of the population corresponds to each subgroup. Finally, a sample is obtained such that the proportions in the sample exactly match the proportions in the overall population.
Proportionate Stratified Random Sampling
_______ is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.
Cluster Sampling
Non-Probability Sampling Techniques
- Convenience Sampling
- Quota Sampling
- Network Sampling/Snowball Sampling
In _______, researchers simply use as participants those individuals who are easy to get. People are selected on the basis of their availability and willingness to respond.
Convenience Sampling
_______ is a non-probability sampling method that relies on the non-random selection of a predetermined number or proportion of units.
Quota Sampling
______ is a non-probability sampling method where new units are recruited by other units to form part of the sample. _______ can be a useful way to conduct research about people with specific traits who might otherwise be difficult to identify.
Network Sampling/Snowball Sampling
A sample is obtained using a random process to select participants from a list containing the total population. The randm process ensures that each individual has an equal and independent chance of selection.
Simple Random
A sample is obtained by selecting every nth participant from a list containing the total population after a random start.
Systematic
A sample is obtained by dividing the population into subgroups (strata) and then randomly selecting equal numbers from each subgroups.
Stratified Random
A sample is obtained by subdividing the population into strata and then randomly selecting from each stratum (single) a number of participants so that the proportions in the sample correspond to the proportions in the population.
Proportionate Stratified
Instead of selecting individuals, a sample is obratined by randomly selecting clusters (preexisting groups) from a list of all the clusters that exist within the population.
Cluster
A sample is obtained by selecting individual participants who are easy to get.
Convenience
A sample is obtained by identifying subgroups to be included, then establishing quotas for individuals to be selected through convenience from each subgroup.
Quota
Strength and Weaknesses
The selection process is fair and unbiased, but there is no guarantee that the sample is representative.
Simple Random
Strength and Weaknesses
An easy method for obtaining an essentially random sample, but the selections are not really random or independent.
Systematic
Strength and Weaknesses
Guarantees that each subgroup will have adequate representation, but the overall sample is usually not representative of the population.
Stratified random
Strength and Weaknesses
Guarantees that the composition of the sample (in terms of the identified strata) will be perfectly representative of the composition of the population, but some strata may have limited representation in the sample.
Proportionate Stratified
Strength and Weaknesses
An easy method for obtaining large, relatively random sample, but the selections are not really random or independent.
Cluster
Streangth and Weaknesses
An easy method for obtaining a simple, but the sample is probably biased.
Convenience
Strength and Weaknesses
Allows a researcher to control the composition of a convenience sample, but the sample probably is biased.
Quota
