Module 2 Flashcards
Stages in Sample Selection (1)
Define target population
Stages in Sample Selection (2)
Select sampling frame
Stages in Sample Selection (3)
Define if probability or non probability
Stages in Sample Selection (4)
Plan procedure for selecting sampling units
Stages in Sample Selection (5)
Determine sample size
Stages in Sample Selection (6)
Select actual sampling units
Stages in Sample Selection (7)
Conduct field work
All items or individuals of interest
Population
A finite subset of statistical individuals obtained from the population
Sample
To select a portion from the population
Sampling
Population pyramids
A. Rapidly Explanding
B. Expanding
C. Stationary
D. Contracting
Probability sampling techniques
Simple random
Systematic
Stratified random
Cluster
Non probability sampling techniques
Quota Snowball Self selection Convenient Purposive
Types of purposive sampling
Extreme case Heterogenous Homogenous Critical case Typical case
It refers to the sampling “lottery method”
Simple random sampling
The population is divided into groups based on some characteristi gs
List of Clients
Strata
Random subsamples of n/N
Stratified Sampling
Every member of the population is assigned to only one group
Cluster sampling
A list of every member of the populating
Intervals
Systemic random sampling
Quota sampling
Proportional quota sampling
Non proportional quota sampling
The population of interest is represented almost exactly by the percentage of each cell in the final survey results
Proportional quota sampling
“Soft quotas”
Captures a minimum number of respondents in a specific group
Non proportional quota sampling
The researchers chooses a sample that is readily available in some non random way
Convenience sampling
The respondents decide whether or not to participate
Self selection sampling
It asks respondents to recommend other respondents who might subsequently be invited to take the survey
Snowball sampling
The interview or study designer chooses sampled units who by their judgement will meet the specific purpose of the survey
Purposive sampling
The goal is not to be representative of views on an issue but “to look at it from all angles”
Maximum variance sampling (heterogenous sampling)
To deeply explore the views if a group of respondents with the same characteristics
Homogenous sampling
It is interested in an in-depth assessment of the typical viewpoits
Typical case sampling
It is interested in understanding unusual cases such as successes or failures
Extreme case sampling
Studying those cases that have the most to offer in terms of understanding the population
Critical case sampling
Surveying experts on a particular topic, with their expertise left to the judgement of the interviewer or study designer
Expert sampling
Surveying every single member of a qualifying subgroup
Total population sampling
Also called “raw data”
Ungrouped data
Data that has not been summarized in any way
Ungrouped data
Example:
Data set: 5, 2, 10, 12, 8, 12
Ungrouped data
Data that has been organized
Grouped data
Ofter called the average of numerical set of data
Mean
Sum of the values / the number of values
Mean
The number that falls in the middle position
The median
The set of data that most frequently appears in the set
Mode
Highest value - lowest value
The range
The ratio if the standard deviation to the mean
Coefficient
