Chapter+9

__Chapter 9: Sampling__
=**1.1** What are the differences between a sample and a population? = Sample: a subset of the population that should represent the entire group. Population: the entire group under study as specified by the research project. = = =**1.2** Indicate the sample frame error typically found in the households listing of a telephone book. = Directories and phone books are readily available but tend to have substantial sample frame error. This is because the larger the sample size the lower the percentage of accuracy will be. The relationship on a graph has curved results as sample size increases and slowly decreases the accuracy on it as well, this is because at a lower sample the accuracy is at it's highest because there is a smaller margin for error, but the margin for error increases at a faster rate the larger the sample becomes. Telephone books are also not an accurate representation of the sample either. Many people have two home phones, or they could have none. There is also unlisted numbers, and old unused phone numbers. Therefore telephone books are not always the most accurate representation.

- //Added by Mike Banelopoulos - 6310031//

=**2.1.** Explain the relationship between sample size and sample accuracy. = Accuracy of a sample: An easy way to interpret the sample error due to the accuracy of the sample is to treat it with a plus-or-minus percentage value. For example, if a sample size with an accuracy level of plus or minus five percent is used, when one analyzes the survey’s findings, they will be about plus or minus five percent of what one would find if I census was performed.

Sample Size is a calculation where n= [(z2 (pq)/(e2)] N= the calculated sample size z= standard error associated with the chosen level of confidence (typically, 1.96) p= estimated percentage in the population q= 100%-p e= acceptable error (desired accuracy level)

Therefore, one would use the sample size as a calculation to determine how many people need to be surveyed and the accuracy would be determined by taking the sample error into consideration.

//**For more examples, see pages 294-296 in the Basic Marketing Research textbook.**//

=**3.1** Why is probability sample also a random sample? = A random sample means that every single member of the population has the same likelihood of being selected for the sample. Probability and random sample are synonymous because probability is the ‘likelihood that something will occur’, therefore meaning the same as random sample.

There are **four probability sampling methods**, they are described as; simple random sampling, systematic sampling, cluster and stratified sampling.

Simple Random Sampling: The researcher uses a table of random numbers, random digit dialing, or some other random selection procedure that guarantees each member of the population has the same chance of being selected into the sample. Systematic Sampling: Uses a list of the members of the population, the researcher selects a random starting point and uses a skip interval, such that will cover the entire list regardless of the starting point. Cluster Sampling: the population is divided into groups called clusters, each cluster must be similar to the other. The researcher then randomly selects a few clusters to conduct a census of each one Scratified Sampling: if the population is believed to have a skewed distribution for one or more of its distinguishing factors, the researcher identifies sub-populations called Strata. A random sample is then taken of each stratum.
 * __Description of methods__:**


 * //For more examples, please see page 301.//**

=//**4.2**// In order to implement a quota sample, what prior knowledge does the researcher need to have about the population? =

A quota sample establishes a specific quota for various types of individuals to be interviewed. Therefore, when a fieldworker begins the process, they will need to use the screening process criteria to determine what they are looking for. Therefore, a screening process needs to be conducted beforehand and the next step is determine what the client is looking for. For example, Caucasian females, between the ages of 15-30. In other words a researcher is given things to look for within a prospect before the researcher conducts anything. The specific quota can only be visuals like age, gender, or race.

//**For more examples, please see page 313.**//