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Sample and sampling methods

this video explains
sampling process
types of sampling technique

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Sample and sampling methods

  1. 1. Sample and Sampling methods Part I
  2. 2. Population Definition: Population is the aggregation of all the units in which the researcher is interested. The term population refers to the aggregate or totality of all the objects, subjects or members who possess similar characteristics.
  3. 3. Types of population Target population: The entire group of people who meet the criteria of the researcher Eg. If the researcher needs to study the problems faced by nursing students in India. In this the population refers to all the Nsg students in India Accessible population It is the subset of target population in which the researcher has accessible. This can be an institution, area, city, state etc Eg. In the above example the accessible population is students of crescent CON.
  4. 4. Sample Definition : It is defined as a representative unit of a target population , which is to be worked upon by researchers during their study Sample consists of subsets of units which comprise the population selected by investigators or researchers to participate in their research project
  5. 5. Sampling process It is the process of selecting observations to provide an adequate description and inferences of the population. Sampling frame: Listing of population from which a sample is chosen
  6. 6. Selection of sample Homogeneous Heterogeneous
  7. 7. Probability sampling methods Random selection of the elements/members of the population In this every subject in a population has equal chance to be selected as study sample Features: Equal chances of being selected Equal opportunity for selection Absence of both systemic and sampling bias Complete elimination of sampling bias
  8. 8. Simple Random Sampling All subsets of the frame are given an equal probability. Methods of selection: Lottery method: Use of table of random numbers Use of computer
  9. 9. Sampling process: ● Identify and define the population ● Determine the desired sample size ● List all members of the population ● Assign all members on the list a consecutive number ● Select an arbitrary starting point from a table of random numbers and read the appropriate number of digits
  10. 10. Advantages ● Minimum knowledge of population ● Easy to analyse data Disadvantages ● Low frequency of use ● Does not require researcher’s expertise ● Larger risk of random error
  11. 11. Stratified random sampling The population is divided into two or more groups called strata according to some criterion such as geographic,location,grade,age..etc…
  12. 12. Selection process ● Identify and define the population ● Determine the desired sample size ● Identify each strata ● Put the entire population in each strata ● Select equal representatives from each strata
  13. 13. Advantages ● Assures representation of all group in sample population ● Characteristics of all stratum can be estimated ● Comparisons can be made between each stratum Disadvantages ● Requires accurate information on proportion of each stratum ● Stratified lists expensive to prepare
  14. 14. Cluster sampling method Process of randomly selecting intact groups, not defined within the defined population sharing similar characteristics It can be ● Neighbourhood ● School ● Districts ● Classroom
  15. 15. Cluster sampling method
  16. 16. Selection process ● Identify and define the population ● Determine the desired sample size ● Identify logical cluster ● Make the whole population into different cluster ● Estimate average number per cluster ● Divide the sample size with number of cluster ● Randomly select the needed sample from each cluster
  17. 17. Advantages ● Can estimate the characteristics of both cluster and population Disadvantages ● Expensive ● Each stage in cluster will induce sampling error
  18. 18. Systematic random sampling Order all units in sampling frame Every nth number on the order list will be taken for study. Eg. Every 3rd person in the list is selected for study.
  19. 19. Selection process ● Identify and define the population ● Make sampling frame ● Determine the desired sample ● Decide on the nth number, in which you are going to select sample ● Select according to the fraction(nth number) ● The first number can be picked randomly
  20. 20. Advantages ● Simple method ● Easy to select ● Evenly spread over entire population ● Cost effective Disadvantages ● Bias may happen ● Each element will not get equal chance ● Ignorance of all element between the nth number
  21. 21. Multistage sampling This method is carried out in different stages Population is divided into multiple clusters and then these clusters are further divided and grouped into various sub groups (strata) based on similarity. One or more clusters can be randomly selected from each stratum. This process continues until the cluster can’t be divided anymore. For example country can be divided into states, cities, urban and rural and all the areas with similar characteristics can be merged together to form a strata.
  22. 22. Advantages ● More accurate ● More effective Disadvantages ● Costly ● Each stage introduce sampling error
  23. 23. Summary ● Population ● Sample ● Sampling process ● Sampling type ● Probability sampling method ● Features of probability sampling ● Types of probability sampling
  24. 24. Thank you