A quick look into the copyrights and how they apply to Hip-Hop in theory and practice - Mikko KapanenFull description
Acceptance sampling for beginners
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purposive samplingDeskripsi lengkap
metode sampling
Laptut Sampling
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SPESIMENDeskripsi lengkap
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under sampling conceptFull description
SAMPLING AND ITS TYPES
SAMPLING Target Population or Universe The population to which the investigator wants to generalize his results Sampling Unit: smallest unit from which sample can be selected Sampling frame The sampling frame is the list from which the potential respondents are drawn
Telephone director List of five star !otel List of student
Sampling sceme Method of selecting sampling units from sampling frame
Sample" all selected respondent are sample
SAMPL# SAMPL# &NIT
SAMPL#
TA$G#T P%P&LATI%N
• A population can be defined as including all people or items with the characteristic one wishes to understand' • (ecause there is ver rarel enough time or mone to gather information from everone or everthing in a population) the goal becomes finding a representative sample *or subset+ of that population'
All university in India
All university Haryana
List of Haryana university
Three university in haryana
SAMPLING ($#A,-%.N
!" Sample# Get information about large populations
Lower cost
More accurac of results
!igh speed of data collection
Availabilit of Population elements'
Less field time
.hen it/s impossible to stud the whole population
SAMPLING……
To whom do ou want to generalize our results0 All 1ive Star !otel All Travel Agenc All !otel 2ustomer
.hen might ou sample the entire population0 .hen our population is ver small .hen ou have e9tensive resources .hen ou don/t e9pect a ver high response
!at is Goo& Sample# The sample must be" 3' representative of the population: ;' appropriately sized *the larger the better+: 7' unbiased: 6' random *selections occur b chance+:
Merits of Sampling Size
of population 1und re
TYPES )- SAMPLE *ASED )N T!) -A+T)(S: T'E (ESP(ESENATI)N *ASIS P$%(A(ILIT= SAMPLING N%N P$%(A(ILIT= SAMPLING ELEMENT SELE+TI)N TE+'NI,E
$#ST$I2T#- SAMPLING &N $#ST$I2T#- SAMPLING
Types of Sampling •Probability
sample – a method of sampling that uses of random selection so that all units/ cases in the population have an equal probability of being chosen. • Non-probability sample – does not involve random selection and methods are not based on Sampling the rationale of probability theory.
Techniques
Probability
NonProbability
Probabilit *$andom+ Samples
Simple random sample
Sstematic random sample
Stratified random sample
2luster sample Simple $andom Sampling
Sstematic Sampling
Proportionate
Probabilit Sampling
Stratified $andom Sampling
2luster Sampling
-is Proportionate
%ne5 Stage
Two Stage
Multi5 Stage
Non5Probabilit Samples
2onvenience samples *ease of access+ sample is selected from elements of a population that are easil accessible
Purposive sample *>udgmental Sampling+ =ou chose who ou thin? should be in the stud
@uota Sampling
Snowball Sampling *friend of friend'etc'+ Non5 Probabilit
2onvenience Sampling
@uota Sampling
>udgment Sampling
Snowball Sampling
Difference .et/een Pro.a.ilit" sampling an& Non Pro.a.ilit"
SIMPLE (AND)M SAMPLING •
Applicable when population is small) homogeneous B readil available
•
All subsets of the frame are given an e
used to determine which units are to be selected' A&vantage #as method to use No need of prior information of population #
-oes not represent proportionate reprenation
Simple random sampling
Ever" su.set of a specifie& si0e n from te population as an e1ual cance of .eing selecte&
Suita.ilit"
This method is suitable for small homogeneous
$andoml selecting units from a sampling frame' C$andom/ means mathematicall each unit from the sampling frame has an e
•
e!ne population
evelop sampling frame
Stages in ran&om sampling:
Assign each unit a number
"andomly select the required amount of random numbers
Systematicall y select random numbers until it meets the sample si#e requirements
(EPLA+EMENT )- SELE+TED UNITS
Sampling schemes ma be without replacement or with replacement
1or e9ample) if we catch fish) measure them) and immediatel return thereplacement water beforedesign) continuing with the sample) thisthem is a to with because we might end up catching and measuring the same fish more than once' !owever) if we do not return the fish to the water *e'g' if we eat the fish+) this becomes a without replacement design'
S"stematic Sampling •
Similar to simple random sample' No table of random numbers D select directl from sampling frame' $atio between sample size and population size
-efine population
-evelop sampling frame
-ecide the sample size
.or? out what fraction of the frame the sample size represents
Select according to fraction *388 sample from 3)888 frame then 38E so ever 38th unit+
1irst unit select b random numbers then ever nth unit selected *e'g' ever th
38 +
S"stematic Sampling AD2ANTAGES:
Sample eas to select
Suitable sampling frame can be identified easil
Sample evenl spread over entire reference population 2ost effective
DISAD2ANTAGES:
Sample ma be biased if hidden periodicit in population coincides with that of selection'
#ach element does not get e
Ignorance of all element between two n element
Systematic sampling
#ver member * for e9ample" ever ;8th person+ is selected from a list of all population members'
Stratifie& (an&om Sample
The population is divided into two or more groups called strata) according to some criterion) such as geographic location) grade level) age) or income) and subsamples are randoml selected from each strata'
Stratied Random Sample Stratified random sampling can be classified in to a% Proportionate stratifie& sampling It involves drawing a sample from each stratum in proportion to the letter/s share in total population tionate stratifie& sampling b' Dispropor proportionate representation is not given to strata
it necesser involves giving over representation to some strata and under representation to other'
e!ne population
evelop sampling frame according to characteristics required
etermine the proportion of each population variable of interest
Systematic sampling methods can then be follo$ed to select sample unit
ST$ATI1I#- SAMPLING A&vantage : Enancement of representativeness to eac sample 'iger statistical efficienc" Eas" to carr" out Disa&vantage:
+lassification error Time consuming an& e3pensive Prior 4no/le&ge of composition an& of &istri.ution of population
+LUSTE( SAMPLING
2luster sampling is an e9ample of Ftwo5stage samplingF ' 1irst stage a sample of areas is chosen: Second stage a sample of respondents within those areas is selected' Population divided into clusters of homogeneous units) usuall based on geographical contiguit' Sampling units are groups rather than individuals'
A sample of such clusters is then selected'
All units from the selected clusters are studied'
The population is divided into subgroups *clusters+ li?e families' A simple random sample is ta?en of the subgroups and then all members of the cluster selected are surveed
%luster sampling Section 1
Section 2
Section 3
Section 5 Section 4
2L&ST#$ SAMPLING' Advantages " 2uts down on the cost of preparing a sampling frame' This can reduce travel and other administrative costs' -isadvantages" sampling error is higher for a simple random sample of same size' %ften used to evaluate vaccination coverage in #PI
+luster6 multi5stage ran&om sample •
+luster sampling" selecting a sample based on specific) naturall occurring groups *clusters+ within a population'
5 #9ample" randoml selecting ;8 hospitals from a list of all hospitals in #ngland' Multi5stage sampling " cluster sampling repeated at a number of levels'
#9ample" randoml selecting hospitals b count and then a from each selected hospital'
5
sample of patients
2omple9 form of cluster sampling in which two or more levels of units are embedded one in the other' 1irst stage) random number of districts chosen in all states' 1ollowed b random number of talu?as) villages' Then third stage units will be houses' All ultimate units *houses) for instance+ selected at last step are surveed'
-ifference (etween Strata and 2lusters
Although strata and clusters are both non5overlapping subsets of the population) the differ in several was' All strata are represented in the sample: but onl a subset of clusters are in the sample' .ith stratified sampling) the best surve results occur when elements within strata are internall homogeneous' !owever) with cluster sampling) the best results occur when elements within clusters are internall heterogeneous
Non Pro.a.ilit" +)N2ENIEN+E SAMPLING
Sometimes ?nown as gra. or opportunit" sampling or acci&ental or
apa0ar&
sampling%
Selection of whichever individuals are easiest to reach
It is done at the convenienceH of the researcher 1or e9ample) if the interviewer was to conduct a surve at a
shopping in thewould morning a given da) the people that heshecenter couldearl interview be on limited to those given there at that given time) which would not represent the views of other members of societ in such an area) if the surve was to be conducted at different times of da and several times per wee?' This tpe of sampling is most useful for pilot testing' In social science research) snowball sampling is a similar techni
+onvenience Sampling Adantage! A sample selected for ease of access& immediately 'no$n population group and good response rate. "isadantage! cannot generalise !ndings (do not 'no$ $hat population group the sample is representative of) so cannot move beyond describing the sample. •*roblems of reliability •o respondents represent the
target population •"esults are not generali#able Sunil +umar
Use results that are eas to et
7u&gmental sampling or Purposive sampling
5 The researcher chooses the sample based on who the thin? would be appropriate for the stud' This is used primaril when there is a limited number of people that have e9pertise in the area being researched Selected based on an e9perienced individual/s belief Advantages
(ased on the e9perienced person/s Judgment
-isadvantages
2annot measure the respresentativeness of the sample
,U)TA SAMPLING
The population is first segmented into mutuall e9clusive sub5 groups) Just as in stratified sampling' Then Judgment used to select subJects or units from each segment based on a specified proportion' 1or e9ample) an interviewer ma be told to sample ;88 females and 788 males between the age of 64 and K8' It is this second step which ma?es the techni
T"pes of Non pro.a.ilit" Sampling Designs
,uota sampling
(ased on prespecified
Advantages
2ontains specific subgroups in the proportions desired
Ma reduce bias
eas to manage)
-ependent on subJective decisions
Not possible to generalize
onl reflects population in terms of the
Sno/.all Sampling &seful when a population is hidden or difficult to gain access to' The contact with an initial group is used to ma?e contact with others' $espondents identif additional people to included in the stud The defined target mar?et is small and uni
*otential Sources of ,rror in "esearch esigns Total %rror
,rrors in Hospitality "esearch The total error is the variation bet$een the true mean value in the population of the variable of interest and the observed mean value obtained in the mar'eting research pro-ect. Random sampling error is the variation bet$een the true mean value for the population and the true mean value for the srcinal sample. Non-sampling errors can be attributed to sources other than sampling& and they may be random or nonrandom including errors in problem de!nition& approach& scales& questionnaire design& intervie$ing methods& and data preparation and analysis. on0sampling errors consist of non0response errors and response errors.
Non-response error arises $hen some of the respondents included in the sample do not respond.
Response error arises $hen respondents give inaccurate ans$ers or their ans$ers are misrecorded or misanaly#ed
Sampling %rror and )ondence •
The larger the sample si#e the more li'ely error in the sample $ill decrease. •1ut&
beyond a certain point increasing sample si#e does not provide large reductions in sampling error. •Accuracy
is a re2ection of the sampling error and con!dence level of the data.
,rrors in Sampling
on03bservation ,rrors
Sampling error naturally occurs %overage error people sampled do not match the population of interest 4nderrepresentation on0response $on5t or can5t participate
,rrors of 3bservation
Intervie$ error0 interaction bet$een intervie$er and person being surveyed "espondent error respondents have di6cult time ans$ering the question 7easurement error inaccurate responses $hen person doesn5t understand question or poorly $orded question ,rrors in data collection Sunil +umar
