Sampling
A random sampling technique, such as simple random sampling or stratified random sampling, would be appropriate for surveying 120,000 people to ensure each person in the population has an equal chance of being selected. These techniques help reduce bias and ensure the sample is representative of the population as a whole.
Sociologists often use experimental research techniques to determine possible cause-and-effect relationships. This involves manipulating one variable (the independent variable) to see how it affects another variable (the dependent variable), while controlling for other factors that could influence the outcome. This approach helps to establish more definitive connections between variables in sociological studies.
Winner and loser theory, by Nicholas Rescher, underscores the notion that devising methods for controlling and using new technology is not possible until the technique is introduced. This theory highlights the unforeseeable consequences that arise from introducing a new technology, making it challenging to predict how it will be used or its impact on society.
Post stratification is a statistical technique used to improve the precision of estimates by adjusting sample weights based on known population characteristics. It involves dividing the sample into subgroups (strata) based on certain characteristics and then adjusting the weights of each subgroup to better reflect the overall population. This helps to reduce bias and improve the accuracy of estimates in survey sampling.
The marketing manager is applying a sampling technique to make inferences about the preferences, behaviors, or opinions of the entire customer population. This helps to gain insights and make decisions based on a subset of customers, rather than having to survey every customer individually.
Sampling error occurs when the sampling protocol does not produce a representative sample. It may be that the sampling technique over represented a certain portion of the population, causing sample bias in the final study population.
Random selection is a method of choosing items from a population in a way that each item has an equal chance of being selected. It helps to reduce bias and ensure that the sample is representative of the population. This technique is commonly used in research studies to improve the generalizability of findings.
This technique is used when natural but relatively homogenous groupings are evident in a statistical population. This technique is commonly used in marketing research. The technique splits the population into groups and only a simple random group is selected.
Convenience sampling is most likely to introduce bias because it involves selecting subjects that are readily available and easily accessible. This can result in a non-representative sample that may not accurately reflect the population of interest.
you should find it yourself
A random sampling technique, such as simple random sampling or stratified random sampling, would be appropriate for surveying 120,000 people to ensure each person in the population has an equal chance of being selected. These techniques help reduce bias and ensure the sample is representative of the population as a whole.
When the sales representative gains additional contacts by getting to know the most influential buyers in the sales territory
Random sampling is a statistical technique used to select a subset of individuals from a larger population, ensuring that each member has an equal chance of being chosen. This method helps to minimize bias, making the sample more representative of the entire population. As a result, conclusions drawn from the sample can be generalized to the broader population with greater accuracy. Overall, random sampling enhances the validity and reliability of research findings.
membrane filitration
Whenever it is impractical to measure the characteristics of interest of each member of the population. For example, the populations of most countries are too large for any of the characteristics of all of the people within them to be measured. For that reason, sampling techniques are applied so that representative samples can be obtained of country populations.
Stratified sampling
Sociologists often use experimental research techniques to determine possible cause-and-effect relationships. This involves manipulating one variable (the independent variable) to see how it affects another variable (the dependent variable), while controlling for other factors that could influence the outcome. This approach helps to establish more definitive connections between variables in sociological studies.