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Soujanya Gade

on 10 March 2014

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Transcript of Sampling

Systematic Sampling
Stratified Sampling
Cluster Sampling
Sampling Methods...but why?
Sampling techniques
A sample is “a smaller (but hopefully representative) collection of units from a population used to determine truths about that population” (Field, 2005)
Simple Random Sampling
Systematic Sampling
Stratified Sampling
Cluster Sampling
Non-probability Methods
Probability Methods
List or "sampling frame"
Generate random numbers
Select a random number "k"
Select every kth person
separate population into groups (strata)
randomly select from strata
Convenience Sampling
Purposive Sampling
Simple Random Sample
Choose sample areas
Select sample of participants within that area
Convenience Sample
Selection is based on availability or researcher's judgement
Convenience Sample example
Albert wants to study preschool nutrition and diet.
Recruits students that work in preschools from the CFD department.
Albert wants to conduct a study to investigate discipline methods Head Start parents use.
Albert goes to Head Start schools during pick up and drop off and uses a random number generator to ask parents to complete survey.

5 4 5 3
2 8 4 1
6 1 9 2
Simple random sampling Example
4 4 1 7
2 9 4 1
6 2 9 3
5 8 7 3
2 2 4 1
6 1 9 5
5 4 5 3
2 5 4 1
6 1 9 2
Systematic Sample Example
About the Conclusion...
About the Sample...
Sampling Breakdown
Albert wants to study family interaction and parenting in Montessori Preschools.
All familes' names are complied into a list and Albert picks every 5th family to complete the Family Quality of Life Questionnaire
Stratified Sampling Example
random/non-random selection
The extent to which sample reflects the characteristics of the population selected
The extent to which the results obtained from sample are generalizable to larger population
Albert wants to study the relationships between Head Start teacher's education level and their effectiveness at teaching children prosocial skills.
Albert knows that 40% of the Head Start teacher population is White, that 30% is African American, that 20% is Asian, and 10% is Latina.
Albert separates teachers into groups based on their ethnicity.
For his study he uses a sample of 100 Head Start teachers,
He draws the first 40 White teachers, the first 30 African American teachers, the first 20 Asian teachers, and the first 10 Latina teachers.
Albert makes sure that the sample in his study has the same percentage of teachers in each ethnic group that the population has.
Albert wants to study how parents choose high schools for their children.
Albert wants to make sure that he samples from both low and high income neighborhoods and from all parts of the state of California.
He divides up parents into zip codes and then randomly selects 10 parents in every zip code.
Cluster Sampling Example
Purposive Sampling
Hand pick sample based on purpose of study and what we know about population
Selection based on a characteristic
Purposive Sampling Example
Albert wants to investigate resilience and coping in children with histories of abuse or neglect.
Albert selects foster children (removed from abusive environment) and their teachers to complete questionnaires
Bag of M&M's
Population of interest
Preschool you want to enroll your child in
Each pack of M&M's:
Representative sample of population
Classrooms within the preschool
Colors of M&M's=Ethnicity
Preschool claims that they have ethnicity equally represented in each classroom
true or false
There is no real difference between convenience sampling and purposive sampling
true or false
true or false
true or false
true or false
A “good” sample is one that is representative of the population from which it was selected

In a stratified sample, the researcher selects Kth person
A table of random numbers selects the sample through a purely random, or chance, basis
The sample is the group to which research findings are generalizable
true or false
Full transcript