For Professor Ryan ONLY
lken82
chp14.docxBusiness Research Methods, Ch. 14
· sampling The thread has 3 unread messages.
created by JUDEENE WALKER
Last updated Feb 26, 2015, 10:47 PM
3
· Comment on Feb 25, 2015, 6:45 PM
Message collapsed. Message unread sampling
posted by JUDEENE WALKER at Feb 25, 2015, 6:45 PM
Last updated Feb 25, 2015, 6:45 PM
·
According to our text, the basic idea of sampling is that by selecting some of the elements in a population we might draw conclusions about the entire population. Benefits of sampling includes but not limited to: greater accuracy of results, lower cost and greater speed of data collection.
Probability and non-probability sampling methods were also discussed in this chapter: probability sampling is a sampling technique wherein the samples are gathered in a process that gives ll the individuals in the population equal chances of being selected. Simple random sampling, stratified sampling, luster random and systematic random sampling are types of probability sampling methods.
· Comment on Feb 26, 2015, 7:51 PM
Message collapsed. Message unread Re: sampling
posted by PATRICIA MARCUS at Feb 26, 2015, 7:51 PM
Last updated Feb 26, 2015, 7:51 PM
·
Great post Judeene In statistics and survey methodology, sampling is concerned with the selection of a subset of individuals from within a population to estimate characteristics of the whole population. The three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data. When it comes to the sampling process, it is usually biased since no randomization was used in obtaining the sample. It is also worth noting that the members of the population did not have equal chances of being selected. The consequence of this is the misrepresentation of the entire population which will then limit generalizations of the results of the study.
· Comment on Feb 26, 2015, 10:47 PM
Message collapsed. Message unread Re: sampling
posted by LOUIS DAILY at Feb 26, 2015, 10:47 PM
Last updated Feb 26, 2015, 10:47 PM
Patricia,
Populations can be so large that we really have to use samples.
thanks
Lou
·
The nature of sampling The thread has 5 unread messages.
created by ARIEL SMITH
Last updated Feb 26, 2015, 6:50 PM
5
· Comment on Feb 25, 2015, 1:00 PM
Message collapsed. Message unread The nature of sampling
posted by ARIEL SMITH at Feb 25, 2015, 1:00 PM
Last updated Feb 25, 2015, 1:00 PM
·
According to the text, the basic idea of sampling is that by selecting some of the elements in a population, we may draw conclusions about the entire population. A population is the total collection of elements about which we wish to make some inferences. What is an element of population? A population element is the individual participant or object on which the measurement is taken also known as the unit of study. A census is a count of all the elements in a population. If 4,000 files define the population, a census would obtain information from every one of them. We call the listing of all population elements from which the sample will be drawn the sample frame.
Russell, M., & Airasian, P. Classroom Assessment: Concepts and Applications, 7th Edition. [VitalSource Bookshelf version]. Retrieved from http://online.vitalsource.com/books/9781308263021/page/380
· Comment on Feb 25, 2015, 1:12 PM
Message collapsed. Message unread Re: The nature of sampling
posted by ARIEL SMITH at Feb 25, 2015, 1:12 PM
Last updated Feb 25, 2015, 1:12 PM
·
Why Sample?
According to the text, there are several reasons for sampling, including (1) lower cost, (2) greater accuracy of results, (3) greater speed of data collection, and (4) availability of population elements
1.Lower cost- Researchers can spend less money observing or interviewing a portion of a population rather than the entire population.
2. Accuracy- More than 90 percent of the total survey error in one study was from nonsampling sources and only 10 percent or less was from random sampling error.3 The U.S. Bureau of the Census, while mandated to take a census of the population every 10 years, shows its confidence in sampling by taking sample surveys to check the accuracy of its census. Only when the population is small, accessible, and highly variable is accuracy likely to be greater with a census than a sample
3. Data collection- Sampling's speed of execution reduces the time between the recognition of a need for information and the availability of that information.
4. Availablity- Sampling is the only process possible if the population is infinite. For example, the text uses an eample related to vehicle safety. Safety is a compelling marketing appeal for most vehicles. Yet we must have evidence to make such a claim. So we crash-test cars to test bumper strength or efficiency of airbags to prevent injury. In testing for such evidence, we destroy the cars we test.
Russell, M., & Airasian, P. Classroom Assessment: Concepts and Applications, 7th Edition. [VitalSource Bookshelf version]. Retrieved from http://online.vitalsource.com/books/9781308263021/page/381
· Comment on Feb 26, 2015, 5:27 AM
Message collapsed. Message unread Re: The nature of sampling
posted by ERIK SEIDEL at Feb 26, 2015, 5:27 AM
Last updated Feb 26, 2015, 5:27 AM
·
Hi Ariel,
This is a nice summary regarding the benefits of sampling. I think there are also some challenges that go along with sampling depending on the type of study. You may be trying to answer a specific research question but know that only certain people in the population would be appropriate to survey in order to form a valid conclusion. For example, if a company were seeking to determine the long-term health impacts of smoking, it would first need to know which members of the population have smoked for a certain number of years. This type of information may be difficult to determine. Health care organizations have an advantage because they have the ability to ask every single patient whether or not they smoke and how long they have smoked. People are much more willing to provide health information to a doctor than to an anonymous survey. This is another important consideration. If the survey originates from the wrong source, it may receive much fewer results.
· Comment on Feb 26, 2015, 12:20 PM
Message collapsed. Message unread Re: The nature of sampling
posted by STEPHANIE RECTOR at Feb 26, 2015, 12:20 PM
Last updated Feb 26, 2015, 12:20 PM
·
Those are some very valid points Ariel and Eric. Coming from a healthcare background Eric, I agree that healthcare organizations definitely have an advantage asking such sensitive questions regarding ones health. Whether it's smoking, drinking, eating habits, etc., a population as a whole is more inclined to give honest feedback to their physician than to an anonymous surveyor. When I was in the sleep diagnostic field, many of our physicians administered sleep questionairs (that we provided) for all of their patients. Whether a patient was coming in for a general physical, or an eye infection, they were given these 20 questions to answer. Because historically sleep apnea had been under diagnosed, our physicians were surprised to see the results of their patients and the concluding results of their sleep studies. They placed a great deal of value on these surveys because they were able to be proactive in patient's overall health. Long term sleep apnea leads to heart conditions, strokes, and possibly death, so an early diagnosis and treatment was imperative. Those questionairs served as a tool that was provided to each and every patient in their database.
· Comment on Feb 26, 2015, 6:50 PM
Message collapsed. Message unread Re: The nature of sampling
posted by LOUIS DAILY at Feb 26, 2015, 6:50 PM
Last updated Feb 26, 2015, 6:50 PM
Ariel,
Yes, sampling is a useful time savings tool.
thanks
Lou
·
Sample vs. Census The thread has 2 unread messages.
created by ARIEL SMITH
Last updated Feb 26, 2015, 6:50 PM
2
· Comment on Feb 25, 2015, 1:16 PM
Message collapsed. Message unread Sample vs. Census
posted by ARIEL SMITH at Feb 25, 2015, 1:16 PM
Last updated Feb 25, 2015, 1:16 PM
·
According to the text, the advantages of sampling over census studies are less compelling when the population is small and the variability within the population is high. A census must follow to conditions (1) feasible when the population is small and (2) necessary when the elements are quite different from each other. When the population is small, any sample we draw may not be representative of the population from which it is drawn. The resulting values we calculate from the sample are incorrect as estimates of the population values. The size of a population determines if a census is feasible.
Russell, M., & Airasian, P. Classroom Assessment: Concepts and Applications, 7th Edition. [VitalSource Bookshelf version]. Retrieved from http://online.vitalsource.com/books/9781308263021/page/381
· Comment on Feb 25, 2015, 7:33 PM
Message collapsed. Message unread Re: Sample vs. Census
posted by JUDEENE WALKER at Feb 25, 2015, 7:33 PM
Last updated Feb 25, 2015, 7:33 PM
·
Census and sampling are methods of collecting data from a population. A census is a periodic collection of information from the entire population; It is also known as a complete enumeration. A census is a time consuming affairs as it involves counting all items, most researcher are always short on time and money so the census is not a frequently used method.
A sample is a subset of units in a population that are selected to represent all units in the population of interest. Unlike a census a sample is a partial enumeration (as it is a count from a part of the entire population). A sample must be robust in its design and large enough to provide a good representative of the entire population of interest.
Advantages of census over a sample;
2. census provides a true measure of the population, reducing sampling error.
2. Increase confidence interval: conducting a census often results in enough respondents to allow a high degree of statistical confidence in the survey results.
When deciding between the two methods, be sure to keep in mind the goals of the present survey and other surveys along the line that will rely on the data being collected.
2. Comment on Feb 26, 2015, 1:41 PM
Message collapsed. Message read Re: Sample vs. Census
posted by ARACHEAL VENTRESS at Feb 26, 2015, 1:41 PM
Last updated Feb 26, 2015, 1:41 PM
4.
Judeene
Thanks for your post. Your post caused me to do a little more research in the areas of census vs a sample. I found that there are other reasons why researchers will use a sample vs a census of the population. Disadvantages of using a census are:
Cost: In terms of money, conducting a census for a large population can be very expensive.
Time: A census generally takes longer to conduct than a sample survey.
Response burden: Information needs to be received from every member of the target population.
Control: A census of a large population is such a huge undertaking that it makes it difficult to keep every single operation under the same level of scrutiny and control.
Reference
1. Comment on Feb 26, 2015, 6:50 PM
Message collapsed. Message read Re: Sample vs. Census
posted by LOUIS DAILY at Feb 26, 2015, 6:50 PM
Last updated Feb 26, 2015, 6:50 PM
Ariel,
Yes, if you can measure the whole population, then do it! You won't even need to do a hypothesis test.
thanks
Lou
·
Good sample The thread has 3 unread messages.
created by ARIEL SMITH
Last updated Feb 26, 2015, 6:49 PM
3
. Comment on Feb 25, 2015, 1:24 PM
Message collapsed. Message unread Good sample
posted by ARIEL SMITH at Feb 25, 2015, 1:24 PM
Last updated Feb 25, 2015, 1:24 PM
1.
According tot he text, the way to figuring out if you have a good sample is to ensure the sample represents the characteristics of the population. In measurement terms, the sample must be valid. Validity of a sample depends on two considerations: accuracy and precision.
1. Accuracy- Accuracy is the degree to which bias is absent from the sample. When the sample is drawn properly, the measure of behavior, attitudes, or knowledge of some sample elements will be less than the measure of those same variables drawn from the population. Variations in these sample values offset each other, resulting in a sample value that is close to the population value. An accurate (unbiased) sample is one in which the under estimators offset the over estimators.
2. Precision- A second criterion of a good sample design is precision of estimate. Researchers accept that no sample will fully represent its population in all respects. The numerical descriptors that describe samples may be expected to differ from those that describe populations because of random fluctuations inherent in the sampling process. This is called sampling error or random sampling error and reflects the influence of chance in drawing the sample members. Sampling error is what is left after all known sources of systematic variance have been accounted for.
Russell, M., & Airasian, P. Classroom Assessment: Concepts and Applications, 7th Edition. [VitalSource Bookshelf version]. Retrieved from http://online.vitalsource.com/books/9781308263021/page/383
1. Comment on Feb 26, 2015, 6:31 PM
Message collapsed. Message unread Re: Good sample
posted by PATRICIA MARCUS at Feb 26, 2015, 6:31 PM
Last updated Feb 26, 2015, 6:31 PM
2.
Great post Ariel. Sampling introduces risk into the project: ? Risk that the data sample may not accurately portray the population--there may be inadvertent exclusions, clusters, strata, or other population attributes not understood and accounted for. Risk assessments There are two risk assessments to be made. "Margin of error", which refers to the estimated error around the measurement, observation, or calculation of statistics within the interval of the sample data, and 2. "Confidence interval", which refers to the probability that true population parameters are within the range of the interval. he principle risk is that the sample misrepresents the population. If confidence is stated as 95% for some interval, then there is a 5% chance that the true population parameter lays outside the interval. So therefore the actual size of the population is irrelevant--so long as it is 'large' compared to the sample
1. Comment on Feb 26, 2015, 6:49 PM
Message collapsed. Message unread Re: Good sample
posted by LOUIS DAILY at Feb 26, 2015, 6:49 PM
Last updated Feb 26, 2015, 6:49 PM
Ariel,
Yes and the best way to increase your probability of having a representative sample is to sample randomly.
thanks
Lou
·
Sample size The thread has 2 unread messages.
created by ARIEL SMITH
Last updated Feb 25, 2015, 8:10 PM
2
. Comment on Feb 25, 2015, 1:30 PM
Message collapsed. Message unread Sample size
posted by ARIEL SMITH at Feb 25, 2015, 1:30 PM
Last updated Feb 25, 2015, 1:30 PM
1.
According to the text, Some principles that influence sample size include:
• The greater the dispersion or variance within the population, the larger the sample must be to provide estimation precision. • The greater the desired precision of the estimate, the larger the sample must be.
• The narrower or smaller the error range, the larger the sample must be.
• The higher the confidence level in the estimate, the larger the sample must be.
• The greater the number of subgroups of interest within a sample, the greater the sample size must be, as each subgroup must meet minimum sample size requirements.
Cost considerations influence decisions about the size and type of sample and the data collection methods. Almost all studies have some budgetary constraint, and this may encourage a researcher to use a nonprobability sample. Probability sample surveys incur list costs for sample frames, callback costs, and a variety of other costs that are not necessary when nonprobability samples are used.
Russell, M., & Airasian, P. Classroom Assessment: Concepts and Applications, 7th Edition. [VitalSource Bookshelf version]. Retrieved from http://online.vitalsource.com/books/9781308263021/page/392
1. Comment on Feb 25, 2015, 8:10 PM
Message collapsed. Message unread Re: Sample size
posted by JUDEENE WALKER at Feb 25, 2015, 8:10 PM
Last updated Feb 25, 2015, 8:10 PM
2.
good points Ariel.
Determining sample size is a very important issue when collection data from the population. Before we can calculate a sample size we need to determine a few things about the target population and sample. When samples are too large we waste time, money and resources on the other hand when samples are too small they may lead to inaccurate results.
Before we can calculate the appropriate sample size we need to determine a few things about our target population: we need to determine the population size (how many people fit in the demographic where the data will be retrieved). The margin of error/confidence interval is another feature that needs to be identified before we decide on our sample size. There is no guarantee that sample will be perfect so we need to determine how much error we can accept.
·
