Overview of Probability Sampling Methods

Sure, here is a more concise version for each type of probability sampling, suitable for a SlideShare presentation:

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**Title: Probability Sampling Methods**

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**1. Simple Random Sampling**
- **Description**: Every member of the population has an equal chance of being selected.
- **Example**: Using a random number generator to select 100 employees from a list of 1000.

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**2. Systematic Sampling**
- **Description**: Selecting every nth member after a random start.
- **Example**: Choosing every 10th person in a list of 1000, starting from a randomly selected point between 1 and 10.

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**3. Stratified Sampling**
- **Description**: Dividing the population into subgroups (strata) and sampling from each.
- **Example**: Sampling employees from different departments to ensure all are represented.

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**4. Cluster Sampling**
- **Description**: Dividing the population into clusters and sampling entire clusters.
- **Example**: Selecting several schools randomly and surveying all students within those schools.

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**5. Multi-stage Sampling**
- **Description**: Combining several sampling methods in stages.
- **Example**: Randomly selecting cities, then households within those cities, and finally individuals within those households.

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These descriptions should be brief enough for each slide while providing essential information about each sampling method.

1. Probability Sampling Pre pared by Ms:Anjali Samson

2. DEFINITION

3. A sample is a smaller collection of unite from a population used to determine groups and facts about that population OR A small group of people taken from a larger group and used to represent the larger group is called sample

4. PROBABILITY SAMPLING

5. It is based on the theory of probability It involves 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 It is used to enhance the representativeness of the selected sample for a study

6. Definition of probability sampling

7. A probability sampling is one that have been selected in such a way that every element chosen has a known probability of being included

8. CHARACTERISTICS

9. Each element will have a non zero chance of selection Always involves chance selection of the selection We can estimate the error associated with the sample Only with a probability sample can be estimate the likelyhood that a sample will represent population

10. ADVANTAGES

11. Avoid selection bias Enables generalisation from the sample to the wider population Particularly this sampling techniques reduces the chance of systemic errors The methods minimise the chance of sampling biases

12. DISADVANTAGE

13. Risks omitting important respondent through chance

14. CLASSIFICATION

15. Simple random sampling Cluster /multistage sampling Systemic random Sampling stratified random sampling Sequential sampling

16. Simple random sampling Every member of population has a equal chance of being selected as subject ADVANTAGES Most reliable and unbiased method Requires minimum knowledge of study population Free from sampling error/ bias DISADVANTAGE Need up to date complete list of all the members of population Expensive and time consuming

17. CLUSTER OR MULTISTAGE SAMPLING In very large population, random selection of geography cluster and random selection of subjects from these cluster ADVANTAGES Cheap , quick and easy for a large population Population parameters of population can be estimated for sample size DISADVANTAGE Possibility of high sampling error Chances of least representative sample due to over represented or under represented cluster

18. SYSTEMIC RANDOM SAMPLING Selecting of every KTH case from the group, such as every 10 th person on a patient list on 100 th person ADVANTAGES Convenient and simple to carry out Distribution of sample over entire population DISADVANTAGES Less representative sample its subject are non randomly distributed Sometimes may result in biased sampling

19. STRATIFIED RANDOM SAMPLING Dividing heterogeneous population in strata based on selected traits such as age, gender, habitat and then random selection of sample from each strata ADVANTAGES Ensures representative sample in heterogeneous population Comparison is possible in 2 groups DISADVANTAGE Requires complete information of population Large population is required Chances of faulty classification of strata

20. SEQUENTIAL SAMPLING The investigator initially select small sample and tries to make interferences; if not able to draw resuits , he / she then at subjects until clear cut interferences can be drawn ADVANTAGES Study on best possible smallest sample Facilitates interferences of studies DISADVANTAGE Not possible to study a phenomenon, which needs to be studied one point at time Requires the repeated entry into the field to collect the sample

21. Thank you Brita Tamm 502-555-0152 [email protected] www.firstupconsultants.com