Where results make sense
 About us   |   Why use us?   |   Reviews   |   PR   |   Contact us

# Topic: Simple random sampling

 Algebra ~ High School Assessments ~ Instruction ~ School Improvement in Maryland Simple random sampling, probability sampling, stratified random sampling, systematic sampling and multistage sampling are some of the legitimate sampling methods that are widely used depending on what is being measured. Simple random sampling is defined as sampling a group of n individuals from the population in such a way that every combination of n individuals has an equal chance of being the sample selected. A representative sample is a sample of the population that closely represents the whole population. www.mdk12.org /instruction/curriculum/hsa/algebra/clarification.html   (848 words)

 Statistics Glossary - Sampling Random sampling is a sampling technique where we select a group of subjects (a sample) for study from a larger group (a population). Simple random sampling is the basic sampling technique where we select a group of subjects (a sample) for study from a larger group (a population). Simple random sampling is most appropriate when the entire population from which the sample is taken is homogeneous. www.cas.lancs.ac.uk /glossary_v1.1/samp.html   (1270 words)

 Sampling (statistics) - Open Encyclopedia   (Site not responding. Last check: 2007-11-07) Sampling is that part of statistical practice concerned with the selection of individual observations intended to yield some knowledge about a population of concern, especially for the purposes of statistical inference. The sampling frame must be representative of the population and this is a question outside the scope of statistical theory demanding the judgement of experts in the particular subject matter being studied. In survey sampling, many of the individuals identified as part of the sample may be unwilling to participate or impossible to contact. open-encyclopedia.com /Sampling_(statistics)   (1203 words)

 [No title] Because the sample mean and sample percentage of simple random samples are unbiased estimators of the population mean and population percentage, respectively, they would seem to be reasonable estimators of those parameters. If we are sampling without replacement, we have to inflate the size of the sample to match the size of the population, by imagining we are sampling from a population the same size as the real population, but with a proportion of ones that matches the proportion of ones in the sample. If the sample size is small enough, relative to the size of the population, then the finite population correction is close to one, and the SE of the sample mean essentially depends only on the sample size n, and not the population size N. www.stat.berkeley.edu /users/stark/SticiGui/Text/ch17.htm   (4297 words)

 Probability Sampling Simple random sampling is the simplest form of random sampling. Simple random sampling is simple to accomplish and is easy to explain to others because it is a fair way to select a sample, it is reasonable to generalize the results from the sample back to the population. The problem with random sampling methods when we have to sample a population that's disbursed across a wide geographic region is that you will have to cover a lot of ground geographically in order to get to each of the units you sampled. www.angelfire.com /empire/richardt   (1427 words)

 Simple random sampling in the field Simple random sampling is a type of probability sampling where each sampling location is equally likely to be selected, and the selection of one location does not influence which is selected next. Sampling rhizomatous grasses, mosses, and much of the rest of the plant world by individual is usually not feasible. This is valid simple random sampling, because every part of the study area is equally likely to be sampled and the location of one line does not affect the location of any other line. oregonstate.edu /instruct/bot440/wilsomar/Content/SRS.htm   (2967 words)

 [No title]   (Site not responding. Last check: 2007-11-07) In statistics, a simple random sample from a population is a sample chosen randomly, in which each member of the population has the same probability of being chosen. In small populations such sampling is typically done "without replacement", i.e., one deliberately avoids choosing any member of the population more than once. Conceptually, simple random sampling is the simplist of the probability sampling techniques, but it is seldom used in practice because of application problems. www.informationgenius.com /encyclopedia/s/si/simple_random_sample.html   (188 words)

 Bot 440/540: Using random numbers In simple random sampling, every potential sampling unit (individual or quadrat) has an equal chance of getting selected and the selection of one sampling unit does not affect the chance of selecting another. Equal probability (the "simple" part of simple random sampling) and independence are met by sampling from a uniform statistical distribution. In fact, simple random sampling and random number selection are so intertwined that you might have to go back and forth between the two sections. oregonstate.edu /instruct/bot440/wilsomar/Content/Random.htm   (1042 words)

 Lecture 8 A simple random sampling is a sample chosen so that the probability of selecting each element in the population is the same for each and every element, and the chance of selecting one element is independent of whether some other element is chosen. It shows the sampling distribution of the mean of a simple random sample of size 2 from the population in Table 7.2. Sampling Distribution of the sample mean (normal population): The sample mean is normally distributed, mean of its sampling distribution equals the mean of the population (m), and the standard deviation of its sampling distribution (s www.albany.edu /~aeco320/Lecture80.htm   (252 words)

 Scoop 8 However, in most cases, we want to select a sample from a sampling frame to represent the population from which it is drawn to make inferences about, and generalize results to that population (see definitions of these terms below). Sample - Some part of a population, often used to provide an estimate or estimates of some characteristic(s) of the entire population - a group selected from a larger group in the hope that studying the smaller group will reveal important things about the larger group. Sampling frame - The list or other record of the population from which the sampling units are drawn (note that most often the sampling frame does not include all members of the population of interest). www.tele.sunyit.edu /Scoop8.htm   (596 words)

 Sample (statistics) - Wikipedia, the free encyclopedia A sample is that part of a population which is actually observed. In normal scientific practice, we demand that it is selected in such a way as to avoid presenting a biased view of the population. If the probabilities of different samples are all equal, for example, the method is called simple random sampling. en.wikipedia.org /wiki/Statistical_sample   (101 words)

 [No title]   (Site not responding. Last check: 2007-11-07) Sampling with replacement: The sample is chosen in this way that after select one sample in the population, put it back into the population before choosing another sample from the population. Simple Random Sampling: A simple random sample of say, size n, is chosen from the population in such a way that every random set of n items from the population has an equal chance of being chosen as sample. Proportionate to stratum size: A method when using the stratified sampling method, the size of a sample obtained from a given stratum is proportional to the size of the stratum within the entire population. faculty.smu.edu /tfomby/eco5385/Keys/EX3.aAnswerKey.doc   (206 words)

 Sampling   (Site not responding. Last check: 2007-11-07) In a multistage random sample, a large area, such as a country, is first divided into smaller regions (such as states), and a random sample of these regions is collected. In the second stage, a random sample of smaller areas (such as counties) is taken from within each of the regions chosen in the first stage. Then, in the third stage, a random sample of even smaller areas (such as neighborhoods) is taken from within each of the areas chosen in the second stage. www.stat.yale.edu /Courses/1997-98/101/sample.htm   (589 words)

 (2) SAMPLING   (Site not responding. Last check: 2007-11-07) A random sample would of course be possible but we would much prefer to spread the sampling over all the possible fish and not run the risk of a random sample concentrating on certain types of fish (say many more from the beginning of the run than the end). The essence of sampling efficiently is to use the knowledge of the population or area you intend to sample in a way which will provide you with a reasonably precise estimate of the measurement variable with no inherent bias. Simple Random samples are not always the best way and Stratification of sampling using knowledge of the area to be sampled  is often far more efficient. www.sos.bangor.ac.uk /marine/mb/o1b03/sampling.htm   (1477 words)

 Simple Random Sampling With Replacement   (Site not responding. Last check: 2007-11-07) A simple random sample is one in which each of the possible samples of elements taken from a population of elements has the same probability of selection. In a simple random sample with replacement, any element selected in a sample can be selected again for the same sample. In multistage cluster sampling, simple random sampling with replacement is typically used in all stages of selection but the final stage. www.cdc.gov /epo/dih/MiniModules/pps/SRS_with_replacement.htm   (158 words)

 DQO - Data Quality Objectives Then the total number of samples to be taken are allocated to the strata according to the relative sizes of the strata and the estimated variance in each stratum. This differs from the simple random sampling approach, in which the total number of samples are randomly distributed over the entire decision unit, in that more samples will tend to be focused in areas of higher variability. Note that the error rate in both cases (40% for simple random sampling, 26% for stratified sampling) is higher than the target error rate of 10%; this likely occurs because of the non-normality of the underlying data. dqo.pnl.gov /software/simsite/stratify.htm   (1395 words)

 Index Page Probability sampling is a technique used to ensure that every element in a sample frame has an equal chance of being incorporated into the sample. In both the simple random sampling and the systematic sampling you will be required to generate a list from the sampling frame. In quota sampling, you select sampling elements on the basis of categories that are assumed to exist within a population. www.socialresearchmethods.net /tutorial/Ojwaya/sampling.html   (1167 words)

 Untitled Sampling without replacement makes more sense as a sampling method, but the probabilty calculations are harder, so we usually don't get into this in a first statistics course. In particular, if we have a SRS (simple random sample) without replacement, from a population with variance sigma-squared, the covariance of two of the different sample values is not zero, but is minus sigma-squared divided by the population size minus 1. If we want to do a SRS (simple random sample) of size n from a population, we must draw the sample in such a way that every subset of size n from the population has an equal probability of being chosen as the sample. www.ma.utexas.edu /users/parker/repl.htm   (813 words)

 Sampling and Collecting Data biased sample - sample is not representative of the population from which it is taken because the method used to collect the data contains unwanted influence(s). simple random sampling - the sample is chosen randomly from the population. stratified random sampling - the population is divided into groups (strata) and the data is collected from the strata by simple random sampling. argyll.epsb.ca /jreed/math9/strand4/4106.htm   (499 words)

 Statistics Glossary - sampling Two samples in which the members are clearly paired, or are matched explicitly by the researcher. It is also used when a random sample would produce a list of subjects so widely scattered that surveying them would prove to be far too expensive, for example, people who live in different postal districts in the UK. This sampling technique may well be more practical and/or economical than simple random sampling or stratified sampling. www.stats.gla.ac.uk /steps/glossary/sampling.html   (1219 words)

 Probability Sampling Simple random sampling is simple to accomplish and is easy to explain to others. Because simple random sampling is a fair way to select a sample, it is reasonable to generalize the results from the sample back to the population. Simple random sampling is not the most statistically efficient method of sampling and you may, just because of the luck of the draw, not get good representation of subgroups in a population. www.socialresearchmethods.net /kb/sampprob.htm   (2446 words)

 MMU - Research Design, Biol Sci Stats and RDProbability sampling methods   (Site not responding. Last check: 2007-11-07) Random sampling is much easier to implement if the sampling frame is explicit, random sampling from an implicit list is much more difficult. Simple random sampling is used to determine which members of the regions are included in the final sample. In cluster sampling, the population is divided into groups called clusters, not all of the clusters are sampled. obelia.jde.aca.mmu.ac.uk /rd/sampprob.htm   (700 words)

 Sample Simple random sampling is the most basic: sample points are located, independently of each other, anywhere within the sampling region and all possible sample points have an equal probability of being selected. This will not produce a simple random sample--the points will still be organized by cells in a grid, and hence be dependent on each other's positions--but it often is good enough to use statistical techniques. Random positioning of the grid will result in potentially different numbers of samples each time you try this, but usually the number of samples falls within a predictable range. www.quantdec.com /sample   (2193 words)

 Types of Sampling Simple Random Sampling: A simple random sample (SRS) of size n is produced by a scheme which ensures that each subgroup of the population of size n has an equal probability of being chosen as the sample. A very simple statement of the conclusion is that the variance of the estimator is smaller if it came from a stratified random sample than from simple random sample of the same size. To create a sampling distribution of an estimator for a sample size of 30, we must be able to consider all possible samples of size 30 and base our analysis on how likely each individual result is. www.ma.utexas.edu /users/parker/sampling/srs.htm   (856 words)

 Simple Random Sampling   (Site not responding. Last check: 2007-11-07) A sampling procedure that assures that each element in the population has an equal chance of being selected is referred to as simple random sampling. Some problems that arise from random sampling can be overcome by weighting the sample to reflect the population or universe. For instance, if in our sample of 100 students we ended up with 60% boys and 40% girls, we could decrease the importance of the characteristics for boys and increase those of the girls to reflect our universe, which is 50/50. www.ryerson.ca /~mjoppe/ResearchProcess/SimpleRandomSampling.htm   (435 words)

 Stratified Random Sampling   (Site not responding. Last check: 2007-11-07) In stratified sampling the population of N units is first divided into non-overlapping subpopulations called strata. If sampling from the strata is simple random sampling then whole procedure is called stratified random sampling. Sampling problems may differ markedly within a population (eg people in prisons and people outside). www.csm.uwe.ac.uk /~pwhite/SURVEY1/node29.html   (113 words)

 DOT HS 809 788 Specifically, the statistical formulas for specifying the sampling precision (estimates of sampling variance), given particular sample sizes, are premised on simple random sampling. Unfortunately, random sampling requires that all of the elements in the population have an equal chance of being selected. Once the sample had been geographically stratified with sample allocation proportionate to population distribution, a sample of assigned telephone banks was randomly selected from an enumeration of the Working Residential Hundreds Blocks of the active telephone exchanges within the region. www.nhtsa.dot.gov /PEOPLE/INJURY/research/2003MVOSS-Survey-Vol1/pages/SampleConstruction.htm   (692 words)

Try your search on: Qwika (all wikis)

About us   |   Why use us?   |   Reviews   |   Press   |   Contact us