Chapter 2 Flashcards
Samples
Representative elements of populatok
Sampling
Process of selecting representative elements
Conditions to be considered during sampling
What is population
Sample size
Sampling methods
Target population plus AKA
Population of interested from whom sample is drawn
Reference population
Source population
Study population
Subset of target population
Study participants plus Aka
Subset of study population from whom data is actually collected
Sample population
Sampling frame
List of all elements in target population
Sampling fraction plus formula
Ratio of total population to sample size
2 types of sampling methods
Probability sampling method
Non probability sampling method
Which sampling method to choose depends of presence of
Sampling frame
PSM probability sampling method
When sampling frame is available
Random selection and sample is representative
Inference possible
5 subtypes of psm
Simple
Systematic
Stratified
Cluster
Multi stage
Simple psm plus aka plus steps
Basic
Lottery or draw method
Steps
Find list of target population
Decide on sample size
Apply lottery method
Systemic sampling plus aka plus steps
Aka interval sampling
Steps
Find list
Decide sample size
Calculate sampling fraction k
Randomly select any number below k
Select every kth interval
Stratified sampling plus steps
Applied when we know the population is heterogenous
Steps
Divide population into strata
Apply stratified sampling formula
njth = n x Njth
————
N
Find separate sampling frame
Cluster sampling plus steps
Applied when the population is homogenous to the topic
Doesn’t require sampling frame
Steps
Divide population into clusters
Randomly select clusters
Include all elements of selected cluster
Multi stage
When population is too large
Non probability sampling
When sampling frame is unavailable
Random selection impossible so generalization impossible
5 subdivision of NpSm
Convenience
Volunteer
Judgmental
Quota
Snowball
Convenience plus aka
Selection based on access
When resource and time is short
Accidental or haphazard 
Volunteer sampling
selection from volunteer population
Judgmental sampling
Selection based on the opinion of the researcher also known as purposive sample
Quota sampling 
Fixed share or reservation
Snowball sampling
selection based on recommendation
Errors in research type
Two types sampling error in on sampling error
sampling error plus aka 
Error associated with not examining the whole population
Random error
is minimized by increasing sample size
is the difference between true population parameter and sample statistic
nonsampling error plus aka
Eaters associated with faulty data collection
Biased error
Increasing sample size can’t illuminate the error
