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CHAPTER 9 : Sampling Design - Theory and Practice - Coggle Diagram
CHAPTER 9 : Sampling Design - Theory and Practice
Sampling :question:
selection of some part of the population on basis of which judgment about the entire population made
process of selecting sufficient number of elements from the population
sample selection :arrow_right: sample design
Why sampling :question:
population is dynamic
cost of studying entire population is high
contact whole population is time consuming
enables calculation of sampling errors thus info on characteristic of population more accurate
Population :question:
entire group of people that the research wish to investigate
in term of elements, time, geographical boundaries
Element :question:
each member of the population
Population size :question:
Total number of elements in the population noted as N
Sample :question:
small group drown from the population & contains the characteristics of the population
Subject :question:
each member of the sample
sample size :question:
total number of subjects in the sample noted as "n"
Parameters :question:
characteristics of the population
Statistics
characteristics of the sample
Sampling Frame :question:
complete list of population interest from the sample is drawn. without SF, random sample of population is impossible
Sampling process
Define population
Determine sample frame
Determine sample design
2 major types of technique
Probability
selected using random selection
outcome = representative sample
can be generalized to the target population
Sampling techniques
Simple random
Systematic
Stratified
Cluster
Multistage
Non probability
elements that do not have known chance of being chosen
use in cases if probability not possible to use
Extend bias in selecting sample
Sampling technique
convenient sampling
Judgement Sampling
Quota Sampling
Snowball Sampling
Determine appropriate sample size
Once the above achieve, then execute sampling process
representation of all elements in population which the sample is drawn
can be inaccurate & up2date
Determine sample size
precision of estimate
amount of variability present in data
degree of confidence to estimate true value
Level of precision
estimate the population fall within a range based on sample estimate
offer an interval estimate, which expect the true population
the narrower the interval, the greater the precision
Variablitiy in Data
smaller the dispersion, greater the probabilities the sample mean will be closer to population mean
greater precision, larger sample size needed
Level of Confidence
the narrower the range, the lower the confidence
reflects level of certainty which can state that the estimate of population based on sample statistic, hod true
at least 95 times out of 100 will reflect true population
Types of error in BR
Sampling Error
occur due to selection of some units & non-selection o other unit into sample
reduce as sample size :arrow_up:
Non sampling error
error by the interviewers, data entry operator or researcher
larger the sample size, larger the non sampling error
