Sampling is the process of selecting a subset of individuals from within a population to estimate characteristics of the whole population. The sample size should be large enough to minimize sampling error and be representative of the overall population. An appropriate sample size is typically between 30 to 500 individuals according to guidelines. The sample size can be calculated using formulas that consider the population size, desired margin of error, and confidence level. It is important for the sample to accurately reflect the diversity of the target population.

1. Reporter : GERWIN B. BALAIROS:

2. SAMPLING
SAMPLE
SIZE
SAMPLING
ERROR
ACCESS
TO THE
SAMPLE
REPRESENTATIVENESS
OF THE SAMPLES

3. SAMPLING . . .
The process of selecting a number of individuals for a
study in such a way that the individuals represent the larger
group from which they were selected.
An integral part of research methodology.

4. Why do sampling?
Factors are :
Expense
Time
Accessibility
Availability

5. Sample size
According to Uma Sekaran in Research Method for
Business 4th edition, Roscoe(1975) proposed the rules of
thumb for determining sample size where sample size
larger than 30 and less than 500 are appropriate for most
research, and the minimum size of sample should be
30% of the population.
Depending on the kind of analysis to performed, some
statistical tests will require larger sample.

6. Determined to some extent by the style of the research.
 Survey style – large group
 Ethnographic or qualitative research - small
 Correlational research-no fewer than thirty cases
The size of the samples depends on a number of factors
and the researchers have to give the statistically information
before they can get an answer

7. A sample size can be determined using the Slovins (1960) formula,
which is as follows
n =
𝑁
1+𝑁𝑒2
Where n is the sample size
N is the population
e is the margin of error
1 is a constant value

8. Example :
From the population of 10 000 clients with tuberculosis, a
nurse researcher selected a sample size with a margin of
error of 5%.
The desired sample size is computed to be 385.

9. Sampling Error
The larger the sample size the more likely error in the
sample will decrease.
But, beyond a certain point increasing sample size does not
provide large reductions in sampling error.
Accuracy is a reflection of the sampling error and
confidence level of the data.

10. Errors in Sampling
Non observational errors :
Sampling error : naturally occurs
Coverage error : people sampled do not match the
population of interest
Under representation
Non – response won’t or can’t participate

11. Errors of observation :
 Interview error –interaction between interviewer and
person being surveyed
 Respondent error – respondents have difficult time
answering the question
 Measurement error: inaccurate responses when person
does’nt understand question or poorly worded question
 Errors in data collection
Errors in Sampling

12. The representativeness of the sample
means that the sample must be like the population in as
many ways as possible.
The accessible population must be representative of the
target population.
Example
The population of BSN students is 600 only 200 BSN
students are included as the target population and only 100
students are chosen as samples for the actual study.

13. The access to the sample
oIs a key issue and is an early factor that must be decided in
research.
oNeed to ensure that access is not only permitted but also,
in fact, practicable.
oGuarded by ‘gatekeeper’- people who can control
researchers’ access to those whom they really want to
target.
oRelease of information