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Sampling In Research in Education
Dr. V. K. MAHESHWARI Former Principal K.L.D.A.V. College
ROORKEE (INDIA)
Dr. SURAKSHA BANSAL Principal
Gandhi Inst. of professional &technical stud
MEERUT (INDIA)
Sampling is the act, process, or technique of selecting a suitable sample, or a representative pa a population for the purpose of determining parameters or characteristics characteristics of the who population The process of defining a representative subpopulation to study is called sampling.
Research is an Endeavour to study or obtain knowledge through the use of a systematic appr with with the intent intent of clarif clarifica icatio tion. n. This This includ includes es activ activiti ities es which which attemp attemptt to discov discover er new information, or new applications of existing knowledge
It is a carefu carefull or dilige diligent nt search search,, studio studious us inquir inquiry y or examin examinati ation on especi especiall ally y invest investiga iga experimentation aimed at the discovery and interpretation of facts, revision of accepted theori laws in the light of new facts or practical application of such new or revised theories or laws, i also be the collection of information about a particular subject.
Master your semester with Scribd The Concept of Sample Read Free Foron 30this Days Sign up to vote title & The NewMost York Times Useful Not useful people intuitively understand the idea of sampling. The basic idea of sampling sampling i Special offer for students: Only $4.99/month.
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by selecting some of the elements in a population, we may draw conclusions about the population.
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Sometimes, the entire population will be sufficiently small, and the researcher can include the e population in the study. This type of research is called a census study because data is gathere every member of the population.
Usually, the population is too large for the researcher to attempt to survey all of its members. A s but but carefu carefully lly chosen chosen sample sample can be used used to repres represent ent the the popula populatio tion. n. The sample sample reflec reflec characteristics of the population from which it is drawn.
Since Since it will will not not be practi practical cal to recrui recruitt every every human human for the the study study,, it is necess necessary ary to an accessible population . The accessible population is a subset of the target population that ref specific characteristics with respect to age, gender, diagnosis, etc., and who are accessible for s Cox and West describe a population as a well-defined group of people or objects that share com characteristics. A population population in a research study is a group of individual’s individual’s persons, objects, objects, or from which samples are taken for measurement for example a population of presidents or profes books or students.
A population is group about which which some information information is sought. sought. Most researchers cannot cannot inclu members of the population in their studies and must resort to limiting the number of subjects to o sample from the population It is incumbent on the researcher to clearly define the target popula There There are no strict strict rules to follow follow,, and the resear researche cherr must must rely rely on logic logic and judgmen judgmen population is defined in keeping with the objectives of the study.
A basic principle of sampling is that every member of the population must have an e chance of being included in the sample
The purpose of sampling?
The cost of studying an entire population to answer a specific question is usually prohib in terms of time, money and resources. Therefore, a subset of subjects representative given population must be selected; this is called sampling. The concepts involved in sele Read Free Foron 30this Days Sign up to vote title subjects to represent the larger population are presented
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A sample is a small subset of the population that has been chosen to be studied . The sa
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Main reasons for sampling
There are six main reasons for sampling instead of doing a census. These are; -Economy -Timel -The large size of many populations -Inaccessibility -Inaccessibility of some of the population -Destructiveness -Destructiveness o observation –accuracy
The economic advantage
Obviously, taking a sample requires fewer resources than a census. For example, assume that you are one of the very curious students around. You have heard so much the famous I.I.T and now that you are there, you want to hear from the insiders. You w know what all the students at I.I.T. think about the quality of teaching they receive, you that all the students are different so they are likely to have different perceptions and believe you must get all these perceptions so you decide because you want an indepth of every student, you will conduct personal interviews with each one of them and you the results in 20 days only, let us assume this particular time you are doing your rese Cornell has only 2000 students and those who are helping are so fast at the interviewin that together you can interview at least 10 students per person per day in addition to yo credit hours of course work. You will require 100 research assistants for 20 days and you are paying them minimum wage of Rs5.00 per hour for ten hours (Rs50.00) per p per day, you will require Rs100000 just to complete the interviews, analysis will ju impossible. You may decide to hire additional assistants to help with the analysis at an Rs.100000 and so on assuming you have that amount on your account.
As unrealistic as this example is, it does illustrate the very high cost of census. For the typ information desired, a small wisely selected sample of I.I. T students can serve the purpose. You even have to hire a single assistant. You can complete the interviews and analysis on your Rarely does a circustance require a census of the population, and even more rarely does one ju the expense.
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contagious and it is killing within hours nobody knows what it is. You are requir
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makes it physically impossible to conduct a census. In such a case, selecting a represen sample may be the only way to get the information required from high school students. The partly accessible populations
There are some populations that are so difficult to get access to that only a sample c used. Like people in prison, like crashed airplanes in the deep seas, presidents e.t.c inaccessibility may be economic or time related. Like a particular study population may costly to reach like the population of planets that only a sample can be used. In other ca population of some events may be taking too long to occur that only sample informatio be relied on. For example natural disasters like a flood that occurs every 100 years or tak example of the flood that occurred in Noah’s days. It has never occurred again.
The destructive nature of the observation sometimes the very act of observing the de characteristic of a unit of the population destroys it for the intended use. Good examp this occur in quality control. For example to test the quality of a fuse, to determine whet is defective, it must be destroyed. To obtain a census of the quality of a lorry load of f you have to destroy all of them. This is contrary to the purpose served by quality-co testing. In this case, only a sample should be used to assess the quality of the fuses Accuracy and sampling
A sample may be more accurate than a census. A sloppily conducted census can provid reliable information than a carefully obtained sample.
Concerns in Statstical Sampling
. There are some distinct advantages and disadvantages in using samples. Advantages in that sampling involves a smaller number of subjects and is more time efficient, less c and potentially more accurate (since it is more feasible to maintain control over a sm Read Free For 30 Days Sign up to vote on this title number of subjects). Disadvantages include potential bias in the selection of subjects, w Useful Not useful may lead to error in interpretation of results and decrease in ability Cancel anytime.to generalize the re Special offer for students: Only beyond the$4.99/month. subjects actually studied.
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The reason behind representativeness being the primary concern in statistical sampling i
it allows the researcher to draw conclusions for the entire population. If the sample i
representative of the population, conclusions cannot be drawn since the results tha
researcher obtained from the sample will be different from the results if the entire popul is to be tested. Practicability
Practicability of statistical of statistical sampling techniques allows the researchers to estimate the possible nu
of subjects that can be included in the sample, the type of sampling technique, the duration o
study, the number of materials, ethical concerns, availability of the subjects/samples, the need fo study and the amount of workforce that the study demands.
All these factors contribute to the decisions of the researcher regarding to the study design
Bias and Error in Sampling
A sample is expected to mirror the population from which it comes, however, there guarantee that any sample will be precisely representative of the population from wh comes. Chance may dictate that a disproportionate number of untypical observations w made. In practice, it is rarely known when a sample is unrepresentative and shou discarded. Sampling error
Sampling error is the degree to which a sample might differ from the population. W inferring to the population, results are reported plus or minus the sampling error
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Sampling error comprises the differences between the sample and the population that ar
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Sampling bias is usually the result of a poor sampling plan. The most notable is the b non response when for some reason some units have no chance of appearing in the samp Non sampling error (measurement error)
The other main cause of unrepresentative samples is non sampling error. This type of can occur whether a census or a sample is being used. Like sampling error, non sam error may either be produced by participants in the statistical study or be an innoce product of the sampling plans and procedures.
A non non samp sampli ling ng erro errorr is an erro errorr that that resu result ltss sole solely ly from from the the manne mannerr in wh obser observa vati tion onss are are made. made. The The simp simple lest st exam exampl plee of non samp sampli ling ng erro errorr is in measurements due to malfunctioning instruments or poor procedures. For example, con the observation of human weights. If persons are asked to state their own weights themse no two answers will be of equal reliability. The people will have weighed themselve different different scales in various various states states of poor calibrations. calibrations. An individual’ individual’ss weight fluct diurnally by several pounds, so that the time of weighing will affect the answer. The reading will also vary with the person’s state of undress. Responses therefore will not comparable validity unless all persons are weighed u nder the same circumstances.
In surveys of personal characteristics, unintended errors may result from: -The mann which the response is elicited -The social desirability of the persons surveyed -The pu of the study -The personal biases of the interviewer or survey writer The interviewers effect
No two interviewers are alike and the same person may provide different answers to diff interviewers. The manner in which a question is formulated can also result in inacc responses. Individuals tend to provide false answers to p articular questions.
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is the most difficult to prevent because it results from out right deceit on the part o
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Finally, it should be noted that the personal prejudices of either the designer of the stu the data collector may tend to induce bias. In designing a questionnaire, questions m slanted in such a way that a particular response will be obtained even though it is inaccu
Types of Sampling Models The two types types of sampli sampling ng methods methods,, probab probabili ility ty and nonprob nonprobabi abilit lity, y, are define define presented with their respective types
In Nonprobability sampling , members are selected from the population in some nonran manner manner.. These These includ includee conveni convenience ence sampli sampling, ng, judgme judgment nt sampli sampling, ng, quota quota sampli sampli snowball snowball sampling sampling Nonprobabil Nonprobability ity sampling sampling includes includes convenience convenience sampling, sampling, conse sampling, judgmental sampling, quota sampling and snowball sampling In nonproba sampling, the degree to which the sample differs from the population remains unknown
In probability samples , each member of the population has a known non-zero probabil being selected. Probabili Probability ty methods methods include include random sampling, systematic systematic sampl stratifie stratified d sampling. sampling. Probabilit Probability y sampling sampling includes includes simple simple random sampling, syst sampling, stratified sampling, cluster sampling and disproportional sampling The adva of probability sampling is that sampling error can be calculated The convenient sample
Convenienc Conveniencee sampling is probably probably the most commonly commonly used technique technique in research research today . conven convenien ience ce sampli sampling ng,, subjec subjects ts are select selected ed becaus becausee of their their conven convenien ientt access accessibi ibilit lity y researcher. These subjects are chosen simply because they are the easiest to obtain for the study. technique is easy, fast and usually the least expensive and troublesomeA convenience sample re when when the the more more conven convenien ientt elemen elementar tary y units units are chosen chosen from from a popula populatio tion n for observ observ Convenience sampling is used in exploratory research where the researcher is interested in getti inexpensive approximation of the truth. As the name implies, the sample is selected because the convenient. This Nonprobability method is often used during preliminary research efforts to Read Free For 30 Days Sign required up to vote this title gross estimate of the results, without incurring the cost or time toon select a randomsampl Useful Not useful Cancel anytime. Consecutive sampling is a strict version of convenience sampling where every available subj Special offer for students: Only $4.99/month. sele select cted ed i.e. i.e. the the comp comple lete te acce access ssib ible le popu popula lati tion on is stud studie ied. d. This This is the the best best choi choice ce
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common nonprobability method. The researcher selects the sample based on judgment is usually and extension of convenience sampling Disproportional Sampling
Disproportional sampling is a method that facilitates the difficulty encountered with stra samples of unequal size (2). Suppose, for example, suppose an educational grant has secure secured d that that will will suppor supportt study study of only only 200 member memberss (subje (subjects cts)) and that that the ava population in the Academy is 2,000 individuals, in the available population of 2,000 the 1,700 males and 300 females. females. Since the 200 subjects subjects needed for the study comprise comprise on percent of the available population, then how many of each gender are required? S proportioning suggests that 17/20 (85 percent) of the 200 be males and 3/20 (15 perce females. This would result in approximately 170 males and 30 females. The small numb females probably would not provide adequate representation for drawing conclusions the entire membership.
Fortunately, this effect can be controlled by weighting the data so the males rece proportionally larger mathematical representation in the analysis of scores than the fema
Calculating Calculating proportional proportional weights involves determining determining the probability probability that any one ma fema female le Acad Academ emic ician ian will will be sele select cted ed.. Sele Select ctin ing g 100 male male Acad Academ emic icia ians ns invol invol probability of 100 out of 1,700, or 1 of 17 (1/17). The probability of any one fe Academician being selected is 100 out of 300, or 1 of 3 (1/3). Therefore, each female probability of selection more than five times that of any male
Next, the assigned weights are determined by taking the inverse of these probabilities weight for male scores is 17/1 17, and that for females is 3/1 = 3. This means that whe data are analyzed, each male's score will be multiplied by 17, and each female's score w multiplied by 3. In any mathematical manipulation of the data, the total of the males' s would be larger than the total of the females' scores. Read Free Foron 30this Days Sign up to vote title Random sampling Useful Not useful
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The random random sample sample is the the pures purestt form form of prob probab abil ilit ity y samp sampli ling ng.. Each Each memb member er
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A simple random sample Sheet Music
A simple random sample is obtained by choosing elementary units in search a way that unit in the population has an equal chance of being selected. A simple random sample i from sampling bias. However, using a random number table to choose the elementary can be cumbersome. If the sample is to be collected by a person untrained in statistics instructions may be misinterpreted and selections may be made improperly. Instead of a least of random numbers, data collection can be simplified by selecting say every 10 100th unit after the first unit has been chosen randomly as discussed below. such a proce is called systematic random sampling. A systematic random sample
Systematic sampling is often used instead of random sampling. It is also called an Nth selection technique. After the required sample size has been calculated, every Nth rec selected from a list of population members. As long as the list does not contain any hi order, this sampling method is as good as the random sampling method. Its only adva over the random sampling technique is simplicity. Systematic sampling is frequently us select a specified number of records from a computer file
A system systemati aticc random random sample sample is obtained obtained by select selecting ing one unit unit on a random random basi choosing choosing additional additional elementary elementary units at evenly spaced intervals intervals until the desired desired numb units is obtained. For example, there are 100 students in your class. You want a sample from these 100 and you have their names listed on a piece of paper may be in an alphab order. If you choose to use systematic random sampling, divide 100 by 20, you will g Randomly select any number between 1 and five. Suppose the number you have picked that will be your starting number. So student number 4 has been selected. From ther will select every 5th name until you reach the last one, number one hundred. You will en with 20 selected students.
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because it reduces sampling error. A stratum is a subset of the population that share at
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group C. These groups are referred to as strata. You can then randomly select from stratum a given number of units which may be based on proportion like if group A ha persons while group B has 50, and C has 30 you may decide you will take 10% of eac you end up with 10 from group A, 5 from group B and 3 from group C. Quota sampling
Quota Quota sampli sampling ng is the Nonpro Nonprobabi babili lity ty equival equivalent ent of strati stratifie fied d sampli sampling. ng. Like Like str sampli sampling, ng, the resear researche cherr first first identi identifie fiess the stratu stratums ms and their their propor proporti tions ons as the represented represented in the population. population. Then convenience convenience or judgment judgment sampling is used to sele required number of subjects from each stratum. This differs from stratified sampling, w the stratums are filled by random sampling Quota sampling is sampling is a nonprobability techn used to ensure equal representation of subjects in each layer of a stratified sample groupi A cluster sample
A cluster sample is obtained by selecting clusters from the population on the basis of si random sampling. The sample comprises a census of each random cluster selected example, a cluster may be some thing like a village or a school, a state. So you decide a elementary schools in New Delhi State are clusters. You want 20 schools selected. Yo use simple or systematic random sampling to select the schools, and then every sc selected becomes a cluster. If you interest is to interview teachers on their opinion of new prog progra ram m whic which h has has been been intr introd oduc uced, ed, then then all all the the teac teache hers rs in a clus cluste terr mu interviewed. Though very economical cluster sampling is very susceptible to sampling Like for the above case, you are likely to get similar responses from teachers in one sc due to the fact that they interact with one another.
Cluster sampling is a method used to enable random sampling to occur while limitin time and costs that would otherwise be required to sample from either a very large popul or one that is geographically diverse. Using this method, a one- or two-level randomiz process is used the important element in this processRead is that one oftitle the criteria ha Free Foron 30this Days Sign up toeach vote equal opportunity to be chosen, with no researcher or facility Useful bias. Not useful
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This is information rich cases that manifest the phenomenon intensely, but not extrem such as good students, poor students, above average/below average. Maximum vari sampling this involves purposefully picking a wide range of variation on dimensio interest. This documents unique or diverse variations that have emerged in adapti different conditions. It also identifies important common patterns that cut across varia Like in the example of interviewing Cornell students, you may want to get studen different different nationalit nationalities, ies, professional professional backgrounds, backgrounds, cultures, cultures, work experience experience and the Homogeneous Homogeneous sampling sampling This one reduces reduces variation, variation, simplifie simplifiess analysis, analysis, facilitates facilitates interviewing. Like instead of having the maximum number of nationalities as in the a case of maximum variation, it may focus on o n one nationality say Americans only.
Typical case sampling It involves taking a sample of what one would call typical, norm average for a particular phenomenon, Stratified Stratified purposeful purposeful sampling sampling This illustrates illustrates characteri characteristics stics of particular particular subgr interest and facilitates comparisons between the different groups.
Critical Critical case sampling sampling This permits logical generalization generalization and maximum maximum applicati applicati information to other cases like "If it is true for this one case, it is likely to be true of all cases. You must have heard statements like if it happened to so and so then it can happ anybody. Or if so and so passed that exam, then anybody can pass.
Snowball or chain sampling this particular one identifies, cases of interest from people know people who know what cases are information rich that is good examples for s good interview subjects. This is commonly used in studies that may be looking at issue the homeless households. What you do is to get hold of one and he/she will tell you w the others are or can be found. When you find those others they will tell you where yo get more others and the chain continues. Snowball sampling is a special Nonproba method used when the desired sample characteristic is rare. It may be extremely diffic cost cost prohib prohibiti itive ve to locate locate respond respondent entss in these these situat situation ions. s. Snowba Snowball ll sampli sampling ng rel hniqu referr referrals als from from initia initiall subjec subjects ts to generat generatee additi additional onal subjec sub jects. ts. While Whi letitle this this techni tec que Read Free Foron 30this Days Sign up to vote dramatically lower search costs, it comes at the expense of introducing bias becaus Useful Not useful Cancel anytime. technique itself reduces the likelihood that the sample will represent a good cross se Special offer for students: Only $4.99/month. from the population.
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Random purposeful sampling This adds credibility when the purposeful sample is l than one can handle. Reduces judgment within a purposeful category. But it is no generalizati generalizations ons or representat representativenes iveness. s. Sampling Sampling politicall politically y important important cases This sampli sampling ng attrac attracts ts or avoids avoids attrac attracti ting ng attent attention ion undesir undesired ed attent attention ion by purpos purpos eliminating from the sample political cases. These may be individuals, or localities.
Convenience sampling It is useful in getting general ideas about the phenomenon of int For example you decide you will interview the first ten people you meet tomorrow mor It saves time, money and effort. It is the poorest way of getting samples, has the lo credibility and yields information-poor cases.
Combination or mixed purposeful sampling This combines various sampling strategi achieve the desired sample. This helps in triangulation, allows for flexibility, and m multiple interests and needs. When selecting a sampling strategy it is necessary that it fi purpose of the study, the resources available, the question being asked and the constr being faced. This holds true for sampling strategy as well as sample size.
Sampling Risks
There are two types of sampling risks, first is the risk of acceptance of acceptance of the research hypot and the second is the risk for incorrect rejection . These risks pertain to the possibility when a test is conducted to a sample, the results and conclusions may be different from results and conclusions when the test is condu cted to the entire population.
The risk of incorrect acceptance pertains to the risk that the sample can yield a conclu
that supports a theory about the population when it is actually not existent in the popula On the other hand, the risk of incorrect rejection pertains to the risk that the sample can
a conclusion that rejects a theory about the population when in fact, the theoryholds t Master your semester with Scribd Read Free Foron 30this Days Sign up to vote title the population. & The New York Times Useful Not useful Special offer for students: Only $4.99/month.
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Comparing Comparing the two types of risks, risks, researchers researchers fear the risk of incorrect incorrect rejection rejection more
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The researcher makes several decisions when designing a sample these are represent
exibit shown below the sampling sampling decisions flow from two decisions made in the form
of educational- research question hierarchy, the nature of the educational question an investigative questions that evolve from the research qu estion.
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Educational Research question Hierarchy
Select Sample Type Nonprobability
Define Relevant Population
Probability
Select the Sample Technique
Identify Exi Sample Fra
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Recruitment
Once the decision to use a certain sampling approach has been made, subjects mu recrui recruited ted.. The goal of recrui recruitme tment nt is to obtain obtain a sample sample large enough enough to enable enable statistical analysis and allow subjects to be selected in such a manner as to avoid bia Errors or problems in either of these areas can be prevented with a research design employs controls and a carefully planned sampling technique.
There often is an inverse relationship between the ease of recruitment effort and the su in obtaining data. In survey research, for example, direct personal effort in recruitment is not employed; the recruitment method frequently is comprised of obtaining a mailin and submitting questionnaires to the accessible population via the mail. A frequent draw in this type of recruitment recruitment effort is a very low response rate of 50 to 60 percent Altern subjects are more difficult to recruit when more effort on their part is requested. .
Once the accessible population has been defined, every effort should be made to o subjects in the manner planned. If a systematic random sampling method has been ch and a large proportion of the accessible subjects refuses to participate, then a bias er introduced into the study. In the case of subject refusal, bias is introduced since the reaso their refusal is often universal
Recruitment Recruitment techniques techniques may include personal personal contact, contact, follow-up follow-up phone calls, calls, ince (such as paying subjects for their time or parking), etc. Some researchers even make h visits to potential subjects to explain the research and its importance; others mail adver brochures to make participating seem exciting exc iting and important.
Language also may present a potential difficulty with recruitment. Therefore, a brochu the appropriate foreign language or a staff or volunteer who can translate or interpre foreign language may be required.
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Special offer for students: Only $4.99/month. Exclusion criteria are applied to subjects who generally meet the inclusion criteria but
be excluded because they cannot complete the study or possess unique characteristic
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The question of how large a sample should be is a difficult one. Sample size ca determined by various constraints. For example, the available funding may prespecif sample size. When research costs are fixed, a useful rule of thumb is to spent about one of the total amount for data collection and the other half for data analysis. This cons influences the sample size as well as sample design and data collection procedures.
In general, sample size depends on the nature of the analysis to be performed, the de precision of the estimates one wishes to achieve, the kind and number of comparison will be made, the number of variables that have to be examined simultaneously and heterogeneous a universe is sampled. For example, if the key analysis of a random experiment consists of computing averages for experimental and controls in a projec comparing differences, then a sample under 100 might be adequate, assuming that statistical assumptions hold. In nonnon-ex exper perim imen enta tall rese resear arch, ch, most most ofte often, n, rele relevan vantt vari variab able less have have to be co statistically because groups differ by factors other than chance.
More technical considerations suggest that the required sample size is a function o precision of the estimates one wishes to achieve, the variability or variance, one expe find in the population and the statistical level of confidence one wishes to use. The sa size N required to estimate a population mean (average) with a given level of precision i
The square root of N= (1.96)*(&)/precision Where & is the population standard deviati the four the variable whose mean one is interested in estimating. Precision refers to wid the interval one is willing to tolerate and 1.96 reflects the confidence level.
For example, to estimate mean earnings in a population with an accuracy of Rs.100 per using a 95% confidence interval and assuming that the standard deviation of earnings population is Rs.1600.0, the required sample size is 983:[(1.96)(1600/100)] squared.
Master your semester with Scribd Deciding on a sample size for qualitative inquiry can Read be even difficult Free Foron 30 Days Sign up to more vote this title than quanti because there are no definite rules to be followed. It will depend on what you want to k & The New York Times Useful Not useful the purpose of the inquiry, what is at stake, what will be useful, what will have credib Special offer for students: Only $4.99/month.
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and what can be done with available time and resources. With fixed resources whic
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sample: clearly define the target population, the accessible population and define the and effort that will be employed to recruit subjects for study.
The goals of sampling sampling are to decrease decrease time and money costs, costs, to increase increase the amount o and detail that can be obtained, and to increase accuracy of data collection by preve errors. To accomplish these goals it is necessary to follow these steps:
Clearly define the target population to which the results will be generalized. . An accessible population representative of the target must be defined by addit inclus inclusion ion criter criteria ia with with specif specific ic charac character terist istics ics regard regarding ing the geogra geographi phic, c, social social and frames required for this subpopulation. The sampling process must be defined well ahead of subject selection whether i random (probability) (probability) or nonrandom nonrandom (nonprobabil (nonprobability) ity) approach, and the researchers researchers adhere to a specific technique for recruitment appropriate for that approach. The recrui effort effort must be vigorous enough to assure assure a large enough sample to enable statistica statisticall and must minimize probability of error and bias of selection. • •
•
In conclusion, it can be said that using a sample in research saves mainly on money and if a suitab suitable le sampl sampling ing strate strategy gy is used, used, approp appropria riate te sample sample size size select selected ed and nece precautions taken to reduce on sampling and measurement errors, then a sample should valid and reliable information. Details on sampling can be obtained from the refer included below and many other books on statistics or qualitative research which can be f in libraries.
References
1. Webster, Webster, M. (1985). (1985). Webster`s Webster`s nith nith new collegiate collegiate dictionary. dictionary. Meriam Meriam - Webst 2. Salant, Salant, P. and D. A. Dillman Dillman (1994). (1994). How to to conduct your your own survey. survey. John John Wi Sons, Inc. Read Free Foron 30this Days Sign up to vote title 3. Patt atton, on, M.Q.( .Q.(19 1990 90)). Qual Qualiitati ative eval evalua uattion ionUseful and and resea esNot earruseful ch metho ethods ds.. Cancel anytime. Publications. Newbury Park London New Delhi. Special offer for students: Only $4.99/month. 4. Lapi Lapin, n, L. L. (1987 (1987). ). Stat Statis isti tics cs for for mord morder ern n busi busine ness ss deci decisi sion ons. s. Harc Harcou ourt rt
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10. Schlesselm Schlesselman an JJ. Case-control Case-control studies: Design, conduct, conduct, analysis. analysis. New York: O University Press; 1982.
11. Isaac 5, Michael W. Handbook Handbook in research and evaluation, evaluation, 2nd ed. San Diego: Pub.; 1990:1
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