7a Flashcards
any set of individuals (or objects) having some common observable characteristics.
Population
In most cases, the population is……… that there is absolutely no way that we can study all of it
so large
refers to a portion of the population that is representative of the population from which it was selected.
Sample
has all the important characteristics of the population from which it is drawn.
Representative Sample
is the process of selecting a number of study units from a defined study population
Sampling
(reference population): the population about which an investigator wishes to draw a conclusion.
Target population
(population sampled): Population from which the
sample actually was drawn and about which a conclusion can be made.
Study population
The unit of selection in the sampling process.
Sampling unit
The scheme for selecting the sampling units from the study population.
Sample design
The list of units from which the sample is to be selected.
Sampling frame
قائمة بكل ال study population
When taking a sample, we will be confronted with the following questions:
What is the group of people from which we want to draw a sample?
How many people do we need in our sample?
How will these people be selected?
Sampling techniques
Non-Probability Sampling and Probability Sampling
Non-Probability Sampling decided to
Convenient sampling
Judgmental sampling
Self-selection sampling
Quota sample
Snowball Sampling
The one where the units that are selected for inclusion in the sample are the easiest to access
Convenient sampling
A form of convenience sampling in which the population elements are selected based on the judgment of the researcher
Judgmental sampling
A sample in which the units are not selected completely at random but in terms of a certain number of units in each of a number of categorie
Quota sample:
Studying members of “hidden” populations, e.g., IDUs.
Snowball Sampling
It is not haphazard sampling
Simple random sampling
done in a systematic way to ensure, as far as possible, complete objectivity in the selection of the sample
Simple random sampling
A way of ensuring that all members of the population have an equal chance of being selected.
Simple random sampling
It does not guarantee that the sample will not be different in characteristics from the accessible population.
Simple random sampling
Procedures for Drawing Probability Samples
- Select a suitable sampling frame
- Each element is assigned a number from 1 to N (pop. size)
- Generate n (sample size) different random numbers between
1 and N - The numbers generated denote the elements that
should be included in the sample
The sample is chosen by selecting a random starting point and then picking every ith element in succession from the sampling
frame.
Systematic sampling
is determined by dividing the population
size N by the sample size n and rounding to the nearest integer.
sampling interval,
It may increases the representativeness of the sample.
Systematic sampling
Procedures for Drawing Probability Samples in Systematic sampling
1) Select a suitable sampling frame
2) Each element is assigned a number from 1 to N (pop. size)
3) Determine the sampling interval i:i=N/n. If i is a fraction,
round to the nearest integer
4) Select a random number, r, between 1 and i, as explained in
simple random sampling
5) The elements with the following numbers will comprise the
systematic random sample: r, r+i,r+2i,r+3i,r+4i,…,r+(n-1)i
A two-step process in which the population is partitioned into subpopulations, or strata
Stratified random sampling
The target population is first divided into mutually exclusive and collectively exhaustive subpopulations, or clusters.
Cluster sampling
The clusters are sampled with
probability proportional to size.
More than on type of sampling is done
Multistage sampling
Bias resulting from incompleteness of the sampling frame:
Accessibility bias
Seasonability bias
Volunteer bias
Non-response bias etc.
A major objetctive of Stratified random sampling is
to increase precision without increasing cost.
Bias resulting from incompleteness of the sampling frame:
Accessibility bias
Seasonability bias
Volunteer bias
Non-response bias etc.
Hypothesis are tested through ……… .
statistical analysis
Hypotheses are never proved; rather, they are.
accepted or supported
