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8/8/2019 Population and Sampling Arif
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SC 433-Nursing Research 2SC 433-Nursing Research 2
Population and Sampling
After the completion of theunit-VII student will be able to
Define the concepts related to sampling theory.
Distinguish between probability and non- probability sampling.
Identify several types of samples and describe their main characteristics.
Describe approaches to determining samplesize.
Evaluate the sampling approach in aquantitative research study.
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Some important concepts
± Sampling:
Selecting a group of people, events, behaviors,or other elements with which to conduct astudy.
± Sample:
The selected group of people (or elements) from which data are collected for a study
± Population:
The entire set of individuals (or elements) who (that) met the sampling criteria. Also called target population
± Accessible Population:The portion of the target population to which theresearcher has reasonable access.
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Representativeness
The sample, the accessible population, and
the target population are alike in as many
ways as possible.
±
Needs to evaluate: Setting:
Characteristics of the subjects:
± age
± Gender
± ethnicity ± income
± education
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Reasons for Drawing a
Sample
Less time consuming than a census
Less costly to administer than a census
Less cumbersome and more practical to
administer than a census of the targeted
population
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Types of Samples Used
Nonprobability Sample
± Items included are chosen without regard
to their probability of occurrence
Probability Sample
± Items in the sample are chosen on the
basis of known probabilities
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Types of Sampling Used
Quota
Sampling
Non-ProbabilitySampling
Convenience PurposivePurposive
Probability
Sampling
SimpleRandom
Systematic
Stratified
Cluster NetworkNetwork
(continued)
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Probability Sampling
Items in the sample are chosen based on
known probabilities
Probability Samples
Simple
RandomSystematic Stratified Cluster
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Simple Random Sampling
Every individual or item from the frame
has an equal chance of being selected
Selection may be with replacement or
without replacement
Samples obtained from table of random
numbers or computer random number
generators
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Decide on sample size: n
Divide frame of N individuals into groups
of k individuals: k=N/n
Randomly select one individual from the1st group
Select every k th individual thereafter
Systematic Sampling
N = 64
n = 8
k = 8 First Group
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Stratified Sampling
Divide population into two or more subgroups
(called strata) according to some common
characteristic
A simple random sample is selected from eachsubgroup, with sample sizes proportional to strata
sizes
Samples from subgroups are combined into one
Population
Divided into
4 strata
Sample
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Cluster Sampling
Population is divided into several ³clusters,´
each representative of the population
A simple random sample of clusters is selected
± All items in the selected clusters can be used,
or items can be chosen from a cluster using
another probability sampling technique
Population
divided into
16 clusters. Randomly selected
clusters for sample
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Advantages and Disadvantages
Simple random sampling and systematic
sampling
± Simple to use
± May not be a good representation of the
population¶s underlying characteristics
Stratified sampling
± Ensures representation of individuals
across the entire population
Cluster sampling
± More cost effective
± Less efficient (need larger sample to
acquire the same level of precision)
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Factors Influencing Sample
Size
Effect Size
Type of Study Conducted
Number of Variables
Data Analysis Techniques
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Power Analysis
Standard Power of 0.8
Level of Significance
alpha = .05, .01, .001
Effect Size
.2 Small; .5 Medium; .8 Large
Sample Size
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Thank You
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Research Topic
Group 1: Patient¶s satisfaction and nursing services
Group 2: White coat syndrome and blood pressure in8 to 10 years children
Group 3: Self medication practice in nurses
Group 4: Nurse¶s knowledge and practices about patient¶s medication
Group 5: What is future planning after competitionnursing course?
Group 6: What is the difference in night and morning shifting impact on nurse¶s life?