Lesson 8 Data Sampling Flashcards
Quiz 5
Refer to the method or process of selecting respondents or people to answer questions meant to yield data and information for a research study
SAMPLING
It has been rightly noted that “because many population of interest are too large to work with directly, techniques of statistical sampling have been devised to obtain samples taken from larger population
SAMPLING
Is generally a large collection of individuals or objects that is the main focus of scientific query. example: senior high school students in school
Population
Refers to a portion or part of the
population that is representative of
the population from which it was
selected
Sample
Is smaller, manageable version of
a larger group which are used in
statistical testing when population
sizes are too large
Sample
Example:
STEM 11 SHS
Sample
Refers to the list of members ofsuch population from where you
will get the sample
Sampling frame
Example:
Pilot sections STEM 11 SHS
Sampling frame
beginning of sampling could be traced back to the early political activities of the Americans in 1920 when Literary Digest did a pioneering survey about the American’s citizen favorite among the 1920 presidential candidates
History of sampling
Similar to snow expanding widely or rolling
rapidly, this sampling method does not give a
specific set of samples. This is true for a study
involving unspecified group of people. Dealing
with varied groups of people such as street
children, mendicants, drug dependents, call
center workers, informal settlers, street vendors,
and the like is possible in this kind of nonprobability sampling. Free to obtain data from
any group just like snow freely expanding and
accumulating at a certain place, you tend to
increase the number of people you want to form
the sample of your study.
Snowball Sampling
The willingness of a person as your subject to interact with you counts a lot in this non-probability sampling method. If during the data collection time, you encounter people walking on the school campus, along the corridors, and along the park or neighborhood, and these people who shows willingness to respond to your questions, then you automatically consider them as your respondents.
Availability Sampling
You choose the people whom you are sure could respond to the objectives of your study, like selecting those with rich experience, knowledge or interest in your study.
Purposive or Judgmental Sampling
Since the subjects you expect to participate in the sample size selection are the ones volunteering to constitute the sample, there is no need for you to do any selection process.
Voluntary Sampling
You resort to quota sampling when you think
you know the characteristics of the target
population very well. In this case, you tend to
choose sample members possessing or
indicating the characteristics of the target
population.
Using a quota or specific set of persons
whom you believe to have the characteristics
of the target population involved in the study
is your way of showing that the sample you
have chosen closely represents the target
population as regards such characteristics.
Quota sampling
disregards random selection of subjects. The subjects are chosen based on their availability or the purpose of the study, and in some cases, on the sole discretion of the researcher. This is not a scientific way of selecting respondents. Neither does it offer a valid or an objective way of detecting sampling errors
Non-Probability Sampling
Is a method of sampling that makes you isolate a set of
persons instead of individual members to serve as sample
of 120 of 1,000 students, you can randomly select three
sections with 40 students each to constitute a sample.
This sampling techniques is preferred in heterogeneous
populations because it minimizes selection bias and
ensures that the entire population group is represented.
This method is used when the researcher wants to
understand the existing relationship between two groups.
The researcher can represent even the smallest sub-group
in the population
Cluster Sampling
Is a method of sampling from a population which can
be partitioned into subpopulations. Samples are formed
based on members shared attributes, characteristics such
as age, gender, nationality, job profile, educational level,
skills, etc.
This sampling techniques is preferred in heterogeneous
populations because it minimizes selection bias and
ensures that the entire population group is represented.
This method is used when the researcher wants to
understand the existing relationship between two groups.
The researcher can represent even the smallest sub-group
in the population
Stratified Sampling
Is a statistical method involving a selection of
elements from an ordered sampling frame; it is a
like arithmetic progression
A method where researchers select members
of the population at a regular interval.
For example, if you want to have a sample of 150
respondents, you may select a set of numbers
like 1 to 15, and out of the list of 735 students you
choose your sample by selecting every 15th
person on a list of the population (by interval)
until you complete
Systematic Sampling
is the best type of probability
sampling through which you can choose sample from a
population. Using a pure-chance selection, you assure every
member the same opportunity to be in the sample.
Simple Random Sampling
occurs if the selection does
not take place in the way it is planned; such
error is manifested by strong dissimilarity
between the sample and the samples listed
in the sampling frame. The smaller the
sample size is, the bigger the number of
sampling errors
Sampling error
involves all members listed in the
sampling frame representing a certain
population focused on by your study
Probability sampling or Unbiased Sampling
2 types of sampling strategies
Probability sampling or Unbiased Sampling and Sampling error
