Sampling presentation
- 2. What exactly IS a “sample”?
- 3. Important terms Universe: It refers to the total of the items or units in a field of inquiry. Eg : Number of MBA colleges in Madhya Pradesh = 200. Total number of seats 60x200=12000 students will be the resultant universe.
- 4. Types of Universe • Finite: It consists of fixed number of elements. It is possible to enumerate all the elements. eg: Number of employees in a firm – Number of students in a class – Population of a city
- 5. Types of Universe • Infinite: There are no fixed number of elements. It is not possible to enumerate all the elements. eg: Number of stars in the sky. Rolls of dice.
- 6. Population: • Total of items about which the information is to be obtained. Eg: 1075 total MBA students against 12000 seats.
- 7. Sampling Frame Sampling frame consists of list of items from which the sample is to be drawn. Eg: List of 1075 MBA students/ attendance sheet, Voter ID card, Driving License, Aadhar card, Telephone directory
- 8. Sampling Design • It refers to some technique or procedure the researcher would adopt to select some sampling units. • It is determined before any data are collected.
- 9. Steps in sampling design
- 10. Sources of error in a sample • Systematic bias: Systematic bias results from errors in sampling procedures. – It can’t be reduced or eliminated by increasing the sample size. • Sampling error: It occurs just because of incorrect sampling design. -If sample would be small there may be more chances for errors. -Sampling errors can be reduced or increased by Increasing the sample size.
- 11. Reasons :
- 13. Simple Random Sample Simple random sampling is the basic sampling technique where we select a group of subjects (a sample) for study from a larger group (a population). Each individual is chosen entirely by chance and each member of the population has an equal chance of being included in the sample. eg: Lottery system
- 14. Systematic sampling • Every nth Item has to be selected.
- 15. Stratified Sample Classify population into groups or “strata”.
- 16. Cluster sampling • Randomly choose the groups from the population. • Sample are selected in groups. • Resulting sample will be analyzed on the basis of group data. Cluster is hetergenoeus within itself but when it is compared with other groups it may be homogenous to other groups. • Best example is ‘family’ or set of books from different subjects issued to all the students.
- 17. The Convenience Sample • For this kind of sampling, there should be classification of the population first and then survey can be done. • It is most dangerous as well as most easy way of sampling. Also called as stratified convenience sampling. • Anyone like your friend, neighbour can be surveyed.
- 20. Multi-stage Cluster Sample Sampling is done in many stages.
- 21. The Snowball Sample • Find a few respondents that are relevant to the topic. • From those respondents we can get other respondents who are familiar to him/her.
- 22. The Quota Sample Researcher has to determine about the composition of the population and then define the sample which has the same attributes as in the population.
- 24. There are combinations of sampling designs also: Like: Stratified Random sampling Stratified convenience sampling