2021년 2월 17일 (수) 08:04에 Pythagoras0님의 편집

2021-02-17T08:04:07Z

Pythagoras0: /* 메타데이터 */ 새 문단

2020-12-26T12:15:31Z

메타데이터: 새 문단

Pythagoras0: /* 노트 */ 새 문단

2020-12-21T11:10:38Z

노트: 새 문단

새 문서

== 노트 ==

===위키데이터===
* ID : [https://www.wikidata.org/wiki/Q49908 Q49908]
===말뭉치===
# The probability sampling method is based on the likelihood that each member of a population has an equal chance of being selected to be in the sample.<ref name="ref_d7550b44">[https://baselinesupport.campuslabs.com/hc/en-us/articles/204305705-Sampling-Methods Sampling Methods]</ref>
# Most researchers agree that this form of sampling is the closest to representing the actual population, as human bias is eliminated with the use of computational randomization.<ref name="ref_d7550b44" />
# One of the key advantages of probability sampling is that it is the easiest to measure for error.<ref name="ref_d7550b44" />
# This type of sampling guarantees that each member of a population has an equal chance of being included in the sample.<ref name="ref_d7550b44" />
# The reporter asked a sampling of people about their eating habits.<ref name="ref_ba700038">[https://www.merriam-webster.com/dictionary/sampling Definition of Sampling by Merriam-Webster]</ref>
# a sampling of the menu's entrées We were given a sampling of the food.<ref name="ref_ba700038" />
# With the interest-rate-setting Federal Open Market Committee preparing to meet Dec. 15-16, here is a sampling of what Fed officials have said since their last gathering in November.<ref name="ref_ba700038" />
# Just a sampling of the virus's deadly reach is breathtaking.<ref name="ref_ba700038" />
# If rangeland vegetation was homogeneous, designing a sampling regime would be fairly straightforward.<ref name="ref_26d20229">[https://globalrangelands.org/inventorymonitoring/sampling Rangeland Inventory, Monitoring, and Evaluation: Sampling Concepts]</ref>
# Designing effective sampling regimes to accommodate this inherent variability is the real challenge of rangeland inventory or monitoring programs.<ref name="ref_26d20229" />
# Sampling is a method that allows researchers to infer information about a population based on results from a subset of the population.<ref name="ref_d30209ab">[https://www.displayr.com/what-is-random-sampling/ What is Random Sampling?]</ref>
# There are several different sampling techniques available that can be grouped into two categories as probability sampling, and non-probability sampling.<ref name="ref_d30209ab" />
# In probability sampling, alternatively knows as random sampling, you start with a complete sample frame of all eligible individuals that have an equal chance to be part of the selected sample.<ref name="ref_d30209ab" />
# It is typically assumed that statistical tests contain data that has been obtained through random sampling.<ref name="ref_d30209ab" />
# Field sampling programs provide the information needed to determine the status and dynamics of populations and communities and thus are the basis for many kind of research.<ref name="ref_a37f6b73">[http://www.coastalwiki.org/wiki/Sampling Coastal Wiki]</ref>
# Site selection is an important decision in any sampling program and it should be based to the study objectives.<ref name="ref_a37f6b73" />
# Because most sampling program involves comparisons among sites, they should be physically similar in order to meaningfully compared and to avoid any confound conclusion.<ref name="ref_a37f6b73" />
# Choice of biological units in sampling programs.<ref name="ref_a37f6b73" />
# The book begins with an introduction to standard probability sampling concepts, which provides the foundation for studying samples selected from a finite population.<ref name="ref_6732a9fb">[https://www.wiley.com/en-us/Sampling+Statistics-p-9780470454602 Sampling Statistics]</ref>
# Sampling is frequently used because gathering data on every member of a target population or every product produced by a company is often impossible, impractical, or too costly to collect.<ref name="ref_21907cf1">[https://asq.org/quality-resources/sampling Sampling in Quality Control - What is Quality Sampling?]</ref>
# The primary line of defense against sampling bias is good judgment, based on prior experience dealing with the population being studied.<ref name="ref_2a550a3e">[https://www.kellogg.northwestern.edu/faculty/weber/decs-433/sampling.htm Sampling]</ref>
# From a narrow perspective, if we limit ourselves to one particular way of collecting data, we face a clear trade-off: Large samples limit our exposure to sampling error, but are very costly.<ref name="ref_2a550a3e" />
# In practice, such sampling is almost always done without replacement.<ref name="ref_2a550a3e" />
# In such a case, data is frequently collected using systematic sampling.<ref name="ref_2a550a3e" />
# Stratified sampling techniques are generally used when the population is heterogeneous, or dissimilar, where certain homogeneous, or similar, sub-populations can be isolated (strata).<ref name="ref_dc4ad2f7">[http://www.stat.yale.edu/Courses/1997-98/101/sample.htm Sampling]</ref>
# Simple random sampling is most appropriate when the entire population from which the sample is taken is homogeneous.<ref name="ref_dc4ad2f7" />
# Non-probability Sampling: Why don't we use non-probability sampling schemes?<ref name="ref_d67c0111">[https://web.ma.utexas.edu/users/parker/sampling/srs.htm Types of Sampling]</ref>
# Multi-Stage Sampling: Sometimes the population is too large and scattered for it to be practical to make a list of the entire population from which to draw a SRS.<ref name="ref_d67c0111" />
# The formulas in almost all statistics books assume simple random sampling.<ref name="ref_d67c0111" />
# Unless you are willing to learn the more complex techniques to analyze the data after it is collected, it is appropriate to use simple random sampling.<ref name="ref_d67c0111" />
# In sampling, we assume that samples are drawn from the population and sample means and population means are equal.<ref name="ref_cd207e76">[https://www.statisticssolutions.com/sample-size-calculation-and-sample-size-justification/sampling/ Statistics Solutions]</ref>
# Simple random sampling: By using the random number generator technique, the researcher draws a sample from the population called simple random sampling.<ref name="ref_cd207e76" />
# In this type of sampling method, a researcher starts from a random point and selects every nth subject in the sampling frame.<ref name="ref_cd207e76" />
# Stratified simple random sampling: In stratified simple random sampling, a proportion from strata of the population is selected using simple random sampling.<ref name="ref_cd207e76" />
# See for more information the specific sampling procedure card Retail packages and finished articles Take an appropriate number of cans, bottles, bags or jars as a sample.<ref name="ref_74bd6d47">[https://ec.europa.eu/taxation_customs/dds2/SAMANCTA/EN/GeneralProcedures/SamplingProcedures_EN.htm Sampling procedures]</ref>
# Markov chain sampling methods originated with the work of Metropolis, Rosenbluth, Rosenbluth, Teller and Teller (1953) who proposed an algorithm to simulate a high dimensional discrete distribution.<ref name="ref_137878f4">[https://www.sciencedirect.com/topics/social-sciences/sampling-method Sampling Method - an overview]</ref>
# Under independent sampling from the posterior, which is rarely feasible, this calculation would be justified by classical laws of large numbers.<ref name="ref_137878f4" />
# A sample is collected from a sampling frame, or the set of information about the accessible units in a sample.<ref name="ref_1de0e03f">[https://www.nlm.nih.gov/nichsr/stats_tutorial/section2/mod1_sampling.html Sampling]</ref>
# Probability sampling involves random selection, each person in the group or community has an equal chance of being chosen.<ref name="ref_1de0e03f" />
# Non-probability sampling does not involve random selection and so cannot rely on probability theory to ensure that it is representative of the population of interest.<ref name="ref_1de0e03f" />
# However, many researchers use nonprobability sampling because in many cases, probability sampling is not practical, feasible, or ethical.<ref name="ref_1de0e03f" />
# Sampling is the statistical process of selecting a subset (called a “sample”) of a population of interest for purposes of making observations and statistical inferences about that population.<ref name="ref_3f0b1888">[https://courses.lumenlearning.com/suny-hccc-research-methods/chapter/chapter-8-sampling/ Research Methods for the Social Sciences]</ref>
# The sampling process comprises of several stage.<ref name="ref_3f0b1888" />
# The second step in the sampling process is to choose a sampling frame .<ref name="ref_3f0b1888" />
# Note that sampling frames may not entirely be representative of the population at large, and if so, inferences derived by such a sample may not be generalizable to the population.<ref name="ref_3f0b1888" />
# Random sampling is a part of the sampling technique in which each sample has an equal probability of being chosen.<ref name="ref_4141e402">[https://economictimes.indiatimes.com/definition/Random-Sampling What is Random Sampling? Definition of Random Sampling, Random Sampling Meaning]</ref>
# Random sampling is one of the simplest forms of collecting data from the total population.<ref name="ref_4141e402" />
# Under random sampling, each member of the subset carries an equal opportunity of being chosen as a part of the sampling process.<ref name="ref_4141e402" />
# Hence, some variations when drawing results can come up, which is known as a sampling error.<ref name="ref_4141e402" />
# Cluster sampling works best when the clusters are similar in character to each other.<ref name="ref_9af4466c">[https://www.mathsisfun.com/data/sampling.html Sampling]</ref>
# To understand what sampling error is, you first need to know a little bit about sampling and what it means in survey research.<ref name="ref_29a78118">[https://www.qualtrics.com/experience-management/research/sampling-errors/ Sampling Errors: Definition & 5 Most Common Types]</ref>
# To make sure that your sample is a fair representation, you need to follow some survey sampling best practices.<ref name="ref_29a78118" />
# But there’s more to doing sampling well than just getting the right sample size.<ref name="ref_29a78118" />
# Somewhat confusingly, the term ‘sampling error’ doesn’t mean mistakes researchers have made when selecting or working with a sample.<ref name="ref_29a78118" />
# Sampling, in statistics, a process or method of drawing a representative group of individuals or cases from a particular population.<ref name="ref_4df80869">[https://www.britannica.com/science/sampling-statistics Sampling | statistics]</ref>
# The basic sampling design is simple random sampling, based on probability theory.<ref name="ref_4df80869" />
# In this form of random sampling, every element of the population being sampled has an equal probability of being selected.<ref name="ref_4df80869" />
# Sampling based on probability theory allows the investigator to determine the likelihood that statistical findings are the result of chance.<ref name="ref_4df80869" />
# Another reason for sampling is that not all units in the population can be identified, such as all the air molecules in the LA basin.<ref name="ref_e43a2938">[http://web.csulb.edu/~msaintg/ppa696/696sampl.htm Sampling]</ref>
# However, you must be aware of problems that can arise in systematic random sampling.<ref name="ref_e43a2938" />
# Stratified random sampling: Each unit in the population is identified, and each unit has a known, non-zero chance of being in the sample.<ref name="ref_e43a2938" />
# Instead, you may divide students into the five groups and then select the same number of students from each group using a simple random sampling method.<ref name="ref_e43a2938" />
# Pew Research Center also conducts international surveys that involve sampling and interviewing people in multiple countries.<ref name="ref_cc452016">[https://www.pewresearch.org/methods/u-s-survey-research/sampling/ Sampling - Pew Research Center Methods]</ref>
# Some special challenges arise when sampling these populations.<ref name="ref_cc452016" />
# In particular, it may be difficult to find a sampling frame or list for the population of interest and this may influence how the population is defined.<ref name="ref_cc452016" />
# Non-probability sampling uses non-random techniques (i.e. the judgment of the researcher).<ref name="ref_72366976">[https://www.statisticshowto.com/probability-and-statistics/sampling-in-statistics/ Sampling in Statistics: Different Sampling Methods, Types & Error]</ref>
# In systematic sampling , you select sample elements from an ordered frame.<ref name="ref_72366976" />
# A sampling frame is just a list of participants that you want to get a sample from.<ref name="ref_72366976" />
# In stratified sampling, sample each subpopulation independently.<ref name="ref_72366976" />
# The representation of this two is performed either by the method of probability random sampling or by the method of non-probability random sampling.<ref name="ref_9cb81b29">[https://medcraveonline.com/BBIJ/sampling-and-sampling-methods.html Sampling and sampling methods]</ref>
# The selection of random type is done by probability random sampling while the non-selection type is by non-probability probability random sampling.<ref name="ref_9cb81b29" />
# The aim of this article is to discuss about the sampling and sampling technicality.<ref name="ref_9cb81b29" />
# Statistical agencies prefer the probability random sampling.<ref name="ref_9cb81b29" />
# Sampling helps a lot in research.<ref name="ref_f65f4fd5">[https://towardsdatascience.com/sampling-techniques-a4e34111d808 Sampling Techniques]</ref>
# The process of selecting a sample is known as sampling.<ref name="ref_f65f4fd5" />
# This Sampling technique uses randomization to make sure that every element of the population gets an equal chance to be part of the selected sample.<ref name="ref_f65f4fd5" />
# All the elements of the cluster are used for sampling.<ref name="ref_f65f4fd5" />
# The early part of the chapter outlines the probabilistic sampling methods.<ref name="ref_ce0567a2">[http://www.fao.org/3/w3241e/w3241e08.htm Chapter 7: Sampling In Marketing Research]</ref>
# These include simple random sampling, systematic sampling, stratified sampling and cluster sampling.<ref name="ref_ce0567a2" />
# Thereafter, the principal non-probability method, quota sampling, is explained and its strengths and weaknesses outlined.<ref name="ref_ce0567a2" />
# The statistical aspects of sampling are then explored.<ref name="ref_ce0567a2" />
# Then, because some types of sampling rely upon quantitative models, we’ll talk about some of the statistical terms used in sampling .<ref name="ref_315afa90">[https://conjointly.com/kb/sampling-in-research/ Sampling]</ref>
# Sampling is a method that allows researchers to infer information about a population based on results from a subset of the population, without having to investigate every individual.<ref name="ref_1932ea64">[https://www.healthknowledge.org.uk/public-health-textbook/research-methods/1a-epidemiology/methods-of-sampling-population Methods of sampling from a population]</ref>
# There are several different sampling techniques available, and they can be subdivided into two groups: probability sampling and non-probability sampling.<ref name="ref_1932ea64" />
# In probability (random) sampling, you start with a complete sampling frame of all eligible individuals from which you select your sample.<ref name="ref_1932ea64" />
# Probability sampling methods tend to be more time-consuming and expensive than non-probability sampling.<ref name="ref_1932ea64" />
# Different sampling methods are widely used by researchers in market research so that they do not need to research the entire population to collect actionable insights.<ref name="ref_acff3a36">[https://www.questionpro.com/blog/types-of-sampling-for-social-research/ Types of Sampling: Sampling Methods with Examples]</ref>
# Sampling in market research is of two types – probability sampling and non-probability sampling.<ref name="ref_acff3a36" />
# Probability sampling is a sampling technique where a researcher sets a selection of a few criteria and chooses members of a population randomly.<ref name="ref_acff3a36" />
# In non-probability sampling, the researcher chooses members for research at random.<ref name="ref_acff3a36" />
# Sampling is a process used in statistical analysis in which a predetermined number of observations are taken from a larger population.<ref name="ref_2dfb284f">[https://www.investopedia.com/terms/s/sampling.asp Sampling Definition]</ref>
# Key Takeaways Certified Public Accountants use sampling during audits to determine the accuracy and completeness of account balances.<ref name="ref_2dfb284f" />
# A Certified Public Accountant (CPA) performing a financial audit uses sampling to determine the accuracy and completeness of account balances in the financial statements.<ref name="ref_2dfb284f" />
# Sampling performed by an auditor is referred to as "audit sampling.<ref name="ref_2dfb284f" />
# A commonly seen unit of sampling rate is Hz, which stands for Hertz and means "samples per second".<ref name="ref_76e47172">[https://en.wikipedia.org/wiki/Sampling_(signal_processing) Sampling (signal processing)]</ref>
# Sampling rates higher than about 50 kHz to 60 kHz cannot supply more usable information for human listeners.<ref name="ref_76e47172" />
# Even though ultrasonic frequencies are inaudible to humans, recording and mixing at higher sampling rates is effective in eliminating the distortion that can be caused by foldback aliasing.<ref name="ref_76e47172" />
# For most phonemes, almost all of the energy is contained in the 100 Hz–4 kHz range, allowing a sampling rate of 8 kHz.<ref name="ref_76e47172" />
# One of the problems that can occur when selecting a sample from a target population is sampling bias.<ref name="ref_291ecd42">[https://www.simplypsychology.org/sampling.html Simply Psychology]</ref>
# The sampling frame is the actual list of individuals that the sample will be drawn from.<ref name="ref_5a4d2977">[https://www.scribbr.com/methodology/sampling-methods/ Types and Techniques Explained]</ref>
# Probability sampling means that every member of the population has a chance of being selected.<ref name="ref_5a4d2977" />
# Systematic sampling is similar to simple random sampling, but it is usually slightly easier to conduct.<ref name="ref_5a4d2977" />
# Stratified sampling involves dividing the population into subpopulations that may differ in important ways.<ref name="ref_5a4d2977" />
# In sampling, this includes defining the "population" from which our sample is drawn.<ref name="ref_346e8363">[https://en.wikipedia.org/wiki/Sampling_(statistics) Sampling (statistics)]</ref>
# In such cases, sampling theory may treat the observed population as a sample from a larger 'superpopulation'.<ref name="ref_346e8363" />
# Probability sampling includes: Simple Random Sampling, Systematic Sampling, Stratified Sampling, Probability Proportional to Size Sampling, and Cluster or Multistage Sampling.<ref name="ref_346e8363" />
# Hence, because the selection of elements is nonrandom, nonprobability sampling does not allow the estimation of sampling errors.<ref name="ref_346e8363" />
===소스===
<references />

@@ 114번째 줄: / 114번째 줄: @@
   <references />
-== 메타데이터 ==
+==메타데이터==
 ===위키데이터===
 * ID :  [https://www.wikidata.org/wiki/Q49908 Q49908]

← 이전 판		2020년 12월 26일 (토) 12:15 판
113번째 줄:		113번째 줄:
	===소스===		===소스===
	<references />		<references />
		+
		+	== 메타데이터 ==
		+
		+	===위키데이터===
		+	* ID : [https://www.wikidata.org/wiki/Q49908 Q49908]

표집 - 편집 역사

2021년 2월 17일 (수) 08:04에 Pythagoras0님의 편집

Pythagoras0: /* 메타데이터 */ 새 문단

Pythagoras0: /* 노트 */ 새 문단