Module 6

Population

• The complete set of individuals or elements that possess specific characteristics being studied.

Target Population

• The entire group of people about whom the researcher wants to draw conclusions.

Accessible Population:

• The portion of the target population that is available and accessible to the researcher.

Elements

• The individual units or entities that make up a population (e.g., individual patients).

Participants (Subjects):

• The actual individuals who take part in the research study.

Sample

•  A subset of the population selected to participate in the study.

Sampling

 The process of selecting a portion of the population to represent the whole.

Sampling Plan:

• The detailed blueprint or strategy outlining how the sample will be selected.

External Validity :

• The degree to which study results can be generalized from the sample back to the larger target population. Representative samples are required for strong external validity.

• (Generalizability)

Internal Validity:

• The degree of confidence that the independent variable actually caused the change in the outcome (dependent variable), rather than outside factors.

Sampling Error & Sampling Bias:

•  Errors or biases in how a sample is selected reduce internal validity and accurate representativeness.

Inclusion (Eligibility) Criteria:

• : Strict rules and characteristics that an element must have to be included in the study.

Exclusion Criteria:

• Specific characteristics that prevent an element from being included in the study.

Sampling Frame:

• A comprehensive list of all elements in the population from which the sample is drawn.

Randomization

• The mechanism used to select elements purely by chance.

Simple Random Sampling

1.  Participants are chosen completely at random from a sampling frame.

Stratified Random Sampling:

1. The population is divided into subgroups (strata), and random samples are drawn from each subgroup.

Cluster Sampling:

The population is divided into groups or clusters (e.g., hospitals, schools); entire clusters are then randomly selected.

Systematic Random Sampling:

1. : Participants are selected at regular, defined intervals (using a sampling interval) from an ordered list.

Convenience Sampling:

•  Selecting participants who are readily available and easily accessible.

Quota Sampling:

• Selecting participants non-randomly according to pre-fixed quotas to ensure certain sub-groups are represented.

Purposive Sampling:

• : Hand-picking participants based on specific characteristics or expertise relevant to the study.

Snowball (Network or Chain) Sampling:

• Existing study participants recruit future participants from among their acquaintances.

Theoretical Sampling

• Selecting participants based on emerging concepts during qualitative data analysis.

Nonprobability Sampling

does not require random selection.

Elements do not have an equal chance of being chosen.

Probability Sampling

 when every element in the target population has an equal chance of being selected.

The main goal of a quantitative sample is

representativeness

representativeness

meaning the sample accurately reflects the characteristics of the target population.

Historical Sampling:

•  Selecting historical documents or archival data sources.

Criterion Sampling:

•  Selecting cases that meet a specific, predetermined criterion of importance.

• a qualitative and mixed-methods research strategy where a researcher selects all cases, participants, or events that meet a predetermined standard or threshold of importance

Summary Comparison Table

Feature	Probability Sampling	Nonprobability Sampling
Random Selection Used?
Selection Chance
Sampling Frame Needed?
Main Advantage
Methods Included

Feature	Probability Sampling	Nonprobability Sampling
Random Selection Used?	Yes	No
Selection Chance	Equal for all elements	Unequal / Unknown
Sampling Frame Needed?	Yes	No
Main Advantage	High representativeness & generalizability	Practical, easier, useful for specific qualitative insights
Methods Included	Simple Random, Stratified Random, Cluster, Systematic Random	Convenience, Quota, Purposive, Snowball, Theoretical, Historical, Criterion

Power Analysis:

A statistical calculation used to determine the minimum sample size needed to detect a real effect.

Significance Level:

The risk level accepted for making a Type 1 error.

pre-defined threshold that represents the maximum acceptable risk of committing a Type I error—

Type 1 Error:

Incorrectly rejecting a true null hypothesis (a false positive result).

You conclude that a significant effect, difference, or relationship exists in the population when it actually does not

Effect Size:  

The magnitude or strength of the relationship between variables.

Data Saturation:

Used primarily in qualitative research; data collection stops when no new information or themes emerge.

Homogeneity / Heterogeneity:

How similar (homogeneous) or diverse (heterogeneous) the study population is impacts how large the sample must be to be representative.

Design Factors & Attrition Rate:

Overall study design and the anticipated attrition rate (the percentage of participants who drop out over time) must be factored into the initial sample size calculations.

Participant Recruitment

 process of contacting and enrolling participants.

recruitment goal

to adequately represent the population and meet required sample sizes for power or data saturation.

Effective Recruitment Strategies:Initial Communication: Must be

 pleasant, positive, professional, informative, culturally sensitive, and nonaggressive.

Effective Recruitment Strategies: Informational Materials:

 Use clear handouts or videos

Effective Recruitment Strategies:Tracking Refusals:

Determine reasons for refusal to identify potential sampling biases.

Effective Recruitment Strategies: Incentives

 Offer appropriate rewards or incentives for participation.