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MKG 425 - Study Guide - Final

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FINAL REVIEW MKG 425 (Post- Midterm-Chapters) Chapter 9- Selecting Sample : Concepts important in sampling: population, census, random sample, sample and sampling frame o Population-the entire group under study as defined by research objectives o Census-an accounting of the complete population o Sample- a subset of the population that should represent the entire group o Sampling Frame- list from which the potential respondents are drawn (always draw sampling frame of who you can reach) Sampling Error: error in a statistical analysis arising from the unrepresentativeness of the sample taken o Sample error: any error in a survey that occurs because a sample is used Sampling Frame Error- degree to which the sample frame fails to account for all of the population o (can be prevented to some extent: ie. Greater sample size greater the result) o If you cant apply sample to all population then this is sampling error o Always want error to be small o Almost always there will be sampling error o When sample size increase sample error decreases o Researchers need to choose sample instead of taking the entire population bc of the following: When budget is restricted, human resources are limited, time is limited, sampling is the most efficient versus the entire population; can still obtain information that is suitable and accuracy in a quicker and inexpensive manner o Waste of resources to use the entire population o Sample drawn scientifically, provides accuracy in representing population interest o Assessing all individuals may be impossible, impractical, expensive or inaccurate o Hardly know who makes up entire population o Too costly in terms of HR and other expenses o Time consuming, which adds more cost o Whole population means a lot of error to control and monitor The five steps of Sampling 1. Identify the population o A population is the group of people that you want to make assumptions about 2. Specify a sampling frame o A sampling frame is the group of people from which you will draw your sample. 3. Specify a sampling method o There are basically two ways to choose a sample from a sampling frame: randomly or non-randomly. There are benefits to both. Basically, if your sampling frame is approximately the same demographic makeup as your population, you probably want to randomly select your sample 4. Determine the sample size o In general, larger samples are better, but they also require more time and effort to manage 5. Implement the plan o Once you know your population, sampling frame, sampling method, and sample size, you can use all that information to choose your sample. Researchers define populations in specific terms such as “heads of households located in areas served by the company who are responsible for making the best control decision." Researcher bias, also referred to as experimenter bias- a process where the individual preforming the research influence the results. o Sometimes done to portray a certain outcome Sometimes arises when researcher(s) select subjects that are more likely to generate a desired outcome o Sometimes arises from experimental error & failure to take into account all possible variables *Bias is the one factor that makes qualitative research more dependent upon experience and judgment than quantitative research Sampling bias- a bias in which a sample is collected in such a way that some members of the intended population are less likely to be included than others Two types of sampling include probability and non-probability o Also referred to as random sampling and non-random sampling Probability Sampling Vs. Non-Probability Sampling ∙ Probability sampling- each member has a fixed, known opportunity to belong to the sample ∙ Non-Probability sampling- there is no specific probability of and individual to be a part of the sample.
Basis For Comparison
Probability Sampling
Non-probability Sampling
Meaning:
Sampling technique, in which the subject of the population get an equal opportunity to be selected as a representative sample.
Method of sampling wherein, it is not known that which individual from the population will be selected as a sample.
Alternately known as:
Random Sampling
Non-random Sampling
Basis of selection:
Random
Arbitrarily
Research:
Conclusive
Exploratory
Result:
Unbiased
Biased
Method:
Objective
Subjective
Inferences:
Statistical
Analytical

## How Do You Know When the Results Are Significant?

## What is the size of the sample?

## What is the method (process) for sample selection?

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