Response to the two different discussion postings.

1st posting -

PB

There's a number of sampling types. Probability sampling contains sampling randomly and non-probability sampling doesn't. The research that was conducted highly impacts the type of sampling one uses. To acquire data over a abundant population in which I feel random sampling would be better. In addition there is quota sampling where the person samples the amount of people they need. Target sampling is another one where the individual uses it when targeting certain groups. Researchers would have to choose which method works adequately for the specific data they are looking for. The researchers need to also take into concern the money, recent population, time when making a selection. In order to get more accurate conclusions one needs to analyze all the factors such as: what, when, who and why this research was conducted in order to conclude a proper sampling method.

Representative sampling is samples which represents the entire population This certain sample counterparts the entire population as a whole in its key variables and characteristics which are under examination. "The representative sample lets the researchers better generalize the results of their study to the population as a whole" (Cherry, 2014). The two types of sampling strategies that I am going to discuss is expert sampling which is a selective sampling method and convenience sampling. Convenience sampling is a form of non-probability sampling. The method is generally less expensive and easier. The researcher can clearly stand in one place and ask individuals to take part In a survey. This method can additionally direct towards biased conclusions doesn't represent the entire population as a whole but it permits an individual to accomplish the size of the sample that they want easier and cheaper. In addition this method can also permit access to places where probability sampling cannot. For instance, if you are not able to acquire a certain list of names for a business but you can visit the business during lunch, then convenience sampling can permit you to achieve the data.

Expert sampling is a type of target sampling. This method targets a certain group of individuals. "Expert sampling is used when you are trying to get the opinions of people with a relatively high level of skill or knowledge" (Changing Minds, 2014). For instance, when you view commercials that state 1 in 5 doctors recommend a certain medication. This is a highly used marketing method due to individuals generally respecting and believing in things more when a expert approves of that product. Even though this method seems like it offers opinions better, but one should be careful due to the criteria to be an expert is not always true or strict. A number of experts you view on television are generally not a real expert but nobody ever questions anyone about it, we just tend to believe that because they are perceived as an expert which are more knowledgeable .

2nd posting-

MH

Random sampling is the most simple type of sampling because every member of the population has an equal chance of being chosen. The disadvantages to the random sampling is that it will lack a geographic location and makes it costly due to it being time consuming and costly.

Stratified sampling is superior to random and systematic sampling. The advantages of stratified sampling that it reduces errors. This sampling has groups and subgroups listed within the greater population by what they have in common. There are no disadvantages to this sampling because it reduces the most possible errors.

Researchers go by picking a sampling strategy by determining what factors to use for their research. The research question plays a very important role because without the research question you would have no research to find. It means to have a represenative sample because it's a non biased sample that is being done. It is vital to the outcome of the study because since it isn't biased it gives the population as a whole a chance to do the study which results in less error when doing a sample.