Sampling methods-quantitative&qualitative

2 non-probability sampling methods

-convenience sampling -quota sampling

Stratified random sampling

-define strata of concerns -randomly select the desired number of subjects from each strata

Non-probability sampling

-does not involve random selection -subjects do not have equal chance of being selected in the sample -samples are selected for a specific purpose with a pre-determibed basis of selection -no assurance that the samples represent the population -convenient & economical -potential for bias

Steps of sampling

-identify the population of interest -specify a sampling frame -specify the sampling method **if sampling frame represent your population, use random method. If not, use non randomised method to get a demographic makeup that closer to the population -determine sample size (bigger size better but more time is required

Purposive sampling

-involves obtaining a sample which is linked to the research question -a strategy that hand pick cases that will most benefit the study -researchers may first begin with volunteer informants&receive additional informants through snowballing sampling technique

Systematic sampling

-involves the selection of every kth case from a list of the accessible populations -calculate the sampling fraction: sampling size (200)/population size (1000)=1/5 -get 1 random number between 1-5 as a starting point. eg. choose 3, the subsequent number will be 8 (3+5), 13, 18,23..

Convenience sampling/consecutive

-involves using the most conveniently available people as study participants -getting participants wherever you can find them -includes subject in a study because they happened to be in the right place at the right time eg. A sample of 90 subjects was asked to participate in a study at an immunization booth in the mall pros: -easy to carry out -inexpensive -data can be collected in short duration of time cons: -highly vulnerable to selection bias -available subjects might not represent the target population

Simple random sampling

-most basic probability design -strongest form of sampling in quantitative design -researchers establish a sampling frame (an actual list of all the subjects in the accessible population) -a table of random numbers would be used to draw a sample of the desired size. The required number of the study are randomly selected -use generator of random numbers to get non-repeating random numbers. eg. 5, 33.,27, 99. 58...

2 qualitative sampling designs

-purposive sampling -theoretical sampling

Probability sampling

-random selection of subjects from the population -each person in he population has an equal chance of being selected -more respected approach because it is more likely to produce accurate and representative samples

Quota sampling

-similar to convenience sampling but with an added strategy -identifies population strata such as gender, age & determines how many participants are needed from each stratum -ensures the inclusion of subjects who are likely to be under represented in the convenience sample

4 probability sampling designs

-simple random sampling -systematic sampling -stratified random sampling -cluster sampling

Quantitative sampling designs

Goal: To achieve a sample whose characterisics closely represents he target population 2 categories of sampling designs: -probability sampling -non-probability sampling

Qualitative sampling designs

Goals: a representative sample is needed to ensure that the measurements accurately reflect the population -who would be an information rich data source ? -whom should I talk to so as to maximize my understanding of the phenomena?

strata

mutually exclusive segments of a population based on specified characteristic. eg. using age, gender, ethnic groups/ income level

snowballing sampling technique

relies on participants to refer to others who meet the study eligibility criteria to participate in the study

target population

the entire aggregation of cases which the researcher intends to generalize findings

sampling frame

the group of people from which you will draw your sample

population

the group of people that you want to make assumptions about

accessible population

the portion of the target population, to whom the researcher can gain access to

Cluster sampling

-the subjects from the population is divided according some naturally occuring variable such as geographical area into separate groups, called cluster -a simple random sample is then selected from the population. eg. 20 district, then randomly choose 3: district 3, 7, 18 -larger sample, has north, south, east, west

Theoretical sampling

-used in grounded theory -process of collecting & analyzing data in a simultaneous manner in order to generate a theory eg. a grounded theory study was conducted to develop a theory about responses to hurricane disaster, and a sample was selected to promote generation of the theory. the researcher will continue interviewing the participants until there are no new themes are emerging and all themes are fully explained

What is sampling?

A process of selecting a portion of the population to represent the target population/the process whereby a researcher choose the sample

sample

a portion of the accessible population that reflects the target population