Probability samples have good external validity because they are a representative sample of the population being studied as they are created using random sampling techniques. This means that every member of the population has an equal and independent chance of being chosen to be part of the sample.
This ensures that the sample accurately reflects the population, giving it good external validity. Therefore, the results and conclusions obtained from the sample are likely to generalise to the population, meaning that it has strong external validity.
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What is the main advantage to probability samples?
The main advantage to probability samples is that they provide an unbiased, comprehensive assessment of a population that is representative of the entire population under study. This is because probability samples use random selection, meaning that every individual in the population has an equal probability of being chosen for inclusion in the sample, allowing for a fair representation.
Additionally, probability samples provide data that can be generalized to a larger population with a lower error rate than other methods such as convenience samples. Furthermore, the large sample sizes provided by many probability samples make them highly effective in producing accurate results, ensuring a higher level of confidence in the data collected.
Which type of sampling would increase the external validity of a study?
If the goal of a study is to produce results that are generalizable beyond the sample group being studied, increased external validity is desired. To increase the external validity of a study, one type of sampling that could be used is quota sampling.
Quota sampling requires the researcher to select an equal number of participants from certain categories that represent a known population. This ensures that the sample group is representative of the greater population and thus increases external validity.
Alternatively, stratified sampling could be utilized. Stratified sampling is a technique in which the researcher divides the population of interest into homogeneous subgroups and then draws a sample from each of those subgroups.
By guaranteeing that the sample participants reflect all categories in the studied population, stratified sampling is great for increasing external validity.
Why are probability samples an advantage for the researcher quizlet?
Probability samples provide the researcher with a number of important advantages. First, due to the random selection process, these types of samples often provide the researcher with a more representative group of subjects than other types of samples.
Since subjects in a probability sample are chosen at random, they are seen as being representative of the population in terms of demographic characteristics and other relevant variables. This allows researchers to make stronger inferences from the results of their study.
Second, probability samples often provide greater precision than many other types of samples. By using random selection to pick the subjects, researchers can be sure that their sample is truly random, meaning that it has been chosen with no external biases or influences.
This reduces the potential for errors in the sample and allows researchers to make conclusions with greater accuracy.
Finally, probability samples can often be obtained quickly and inexpensively. The random selection process means that researchers do not have to spend time and resources finding and recruiting people from specific groups or categories.
Since individuals are selected at random, researchers only need a list of a population’s members to generate a sample. This makes probability samples an affordable and practical option for many research projects.
What kind of sample is for external validity quizlet?
External validity refers to the extent to which the results of a study can be generalized to a population beyond the particular participants tested in the study. A sample for external validity quizlet would involve the selection of participants who accurately reflect the characteristics of the population being studied.
For example, if a study was conducted to assess the opinions of a certain age group regarding a given topic, the sample would include participants who represent different ages and backgrounds. Additionally, the sample must be randomly and non-selectively chosen to ensure that it accurately represents the population being studied.
The sample must also be sufficiently large to minimize bias.
