# SAMPLE & SAMPLING.pptx

18 Nov 2022
1 sur 24

### SAMPLE & SAMPLING.pptx

• 1. by Chanchal Pramanick
• 2.  WhatisPopulation ? Population is the whole area on which research is done.  WhatisSample ? Sample is those unit which is selected by researcher from among the population.  WhatisSampling? Sampling is the process to selecting sample on the whole population
• 3. SAMPLE  A population can be defined as including all people or items with the characteristic one wishes to understand.  Because there is very rarely enough time or money to gather information from everyone or everything in a population, the goal becomes finding a representative sample (or subset) of that population. SAMPLE TARGET POPULATION SAMPLE UNIT
• 4. 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 directory List of five star Hotel List of student Sampling scheme : Method of selecting sampling units from sampling frame Sample: all selected respondent are sample
• 5. TYPES OF SAMPLING SAMPLING Probability Non-Probability 1. Simple Random Sampling. 2. Double Random Sampling. 3. Systematic Sampling. 4. Stratified Random Sampling. 5. Cluster Sampling. 6. Multi-Stage Sampling. 1. Judgmental Sampling. 2. Convenient Sampling. 3. Quota Sampling. 4. Snowball Sampling.
• 6. PROBABILITY SAMPLING
• 7. Characteristics According to Good (1966), probability sample have the following characteristics • Each unit in the sample has some known probability of entering the sample. • Weights appropriate to the probabilities are used in the analysis of the sample. • The process of sampling is automatic in one or more steps of selection of units in the sample.
• 8. Advantages • It helps the researcher to know the size of the sample needed to achieve any desired level if accuracy. • The researchers also may be able to specify the chance of each unit being selected. • This method also helps to estimate the magnitude of error due to sampling.
• 9. Disadvantages • It depends upon how good a sampling frame is made, although this remains a limitation in complete enumeration studies. • In this process, only a portion of the sampling frame is examined and so specific information on every sampling unit (people, account, inventory, etc) are ignored. • In small areas or rare sub-population, sampling error may be high. • Representative of the frame may be questionable and controversial.
• 10. 1.Simple RandomSampling A simple random sample is one in which each element of the population has an equal and independent chance of being included in the sample i.e. a sample selected by randomization method is known as simple-random sample and this technique is simple random-sampling. Use only ‘Homogeneous’ group of population. Randomization is a method and is done by using a number of techniques as : (a) Tossing a coin. (b) Throwing a dice. (c) Lottery method. (d) Blind folded method.
• 11. 2.DoubleRandomSampling Use only ‘Homogenous’ group of population.
• 12. 3.Systematic Sampling  Systematic sampling is an improvement over the simple random sampling. This method requires the complete information about the population. There should be a list of information’s of all the individuals of the population in any systematic way. Now we decide the size of the sample. Let sample size = n and Population size = N  Now we select each N/nth individual from the list and thus we have the desired size of sample which is known as systematic sample. Thus for this technique of sampling population should be arranged in any systematic way.
• 13. 4.StratifiedSampling  It is conducted when population is ‘Heterogeneous’.  Researcher divides the whole population into Strata.  ‘Strata’ means layer.  Then he selects the sample according to the proportion of the population from the each strata. Example- Attitude of U.G Students Towards Online Learning. 1000 Girl 600 Boys 400 2 : 3 10 % 100 40 60
• 14. 5.ClusterSampling  Also known as ‘Area sampling’.  Bengali meaning of Cluster is ‘গুচ্ছ’.  Researcher divides the whole population into various zones and then he selects one zone randomly from their.  All the elements of the selected zone is considered as sample.  Not a single element of the selected zone can be throw away. Use ‘Heterogeneous’ group of population. Example- Effect on dengue on West Bengal. E N S W w
• 15. 6.Multi- StageSampling Use ‘Heterogeneous’ group of population. Example- Effect on dengue on West Bengal. E N S W w Randomly selected 1,00,000 5,00,000 10,00,000 15,00,000 10% 10% 10% 10%
• 16. NON-PROBABILITY SAMPLING
• 17. Advantages  They are quicker, cost effective and more convenient than probability samples.  Non-probability samples do not require a sampling frame.  The sample size and quota requirements are usually achieved.
• 18. Disadvantages  Less confidence is placed in the data obtained from samples and thus, results obtained cannot be generalized of the entire population.  Sampling based on convenience affects the variance within groups as well as between groups.  Sampling errors of these sampled cannot be determined.  They depend exclusively on uncontrolled factors and researcher’s insight and there is no statistical method to determine the margin of sampling errors.  Sometimes, such samples are based on absolute frame, which does mot adequately cover the population.  There is considerable scope of bias in the selection of units to be included in the sample.
• 19. 1.JudgmentalSampling  Judgmental sampling also known as ‘Purposive Sampling’. This involves the selection of a group from the population on the basis of available information thought. It is to be representative of the total population. Or the selection of a group by intuition on the basis of criterion deemed to be self- evident. Generally investigator should take the judgment sample so this sampling is highly risky. Apply only small size Population. Example- Effect of parents educational qualification on their child's achievement.
• 20. 2.Convenience Sampling Convenience Sampling also known as ‘Accidental’ or ‘Incidental’ sampling. In convenience sampling, the researcher select those units from the population which are accessible to the researcher. Subjects are chosen simply because they are easy to recruit. This technique is considered easiest, cheapest and least time consuming.
• 21. Consecutive Sampling  A type of convenience sampling. The researcher picks a sample and conduct research over a period of time, collect results, and then moves on to another sample. This sampling technique gives the researcher a chance to work with multiple samples to fine tune his/her research work to collect vital research insights. Small population size.
• 22. 3.QuotaSampling In quota sampling the researcher ensures equal or proportionate representation of subjects depending on which trait is considered as basis of the quota. The bases of the quota are usually age, gender, education, race, religion and socioeconomic status. For example, if basis of the quota is socioeconomic status and the researcher needs equal representation of each quota, (sample size 150), Upper Class- (Elite) 30 Upper Middle Class 30 Lower Middle Class 30 150 Working Class 30 Poor 30
• 23. 4.SnowballSampling  Snowball sampling or chain-referral sampling is defined as a non-probability sampling technique in which the samples have traits that are rare to find. This is a sampling technique, in which existing subjects provide referrals to recruit samples required for a research study.  Snowball sampling method is purely based on referrals  This sampling technique can be extensively used for conducting qualitative research.