Research Methods: Key Concepts and Sampling Techniques

Population

The entire group of individuals a researcher is interested in.

Sample

A subset of the population who participate in the study.

Goal of Sampling

To select a sample that is representative of the population so that the findings from the sample can be generalized back to the larger population.

Reasons for Using Samples

Studying entire populations is often too expensive and impractical due to the large number of individuals involved and the resources required (e.g., time, money).

In-depth Information

Researchers may be able to gather more in-depth information and potentially achieve better data quality by focusing their efforts on a smaller, well-selected sample.

Representative Sample

A sample that accurately reflects the characteristics of the population from which it was drawn.

Importance of Representative Sample

It increases the likelihood that the findings obtained from studying the sample can be generalized to the broader population, enhancing the external validity of the research.

Probability Sampling

Involves methods where every member of the population has a specifiable probability of being selected, and a random process is used for selection.

Simple Random Sampling

An example of probability sampling where each individual has an equal and independent chance of being chosen.

Nonprobability Sampling

Methods that do not involve knowing the probability of selecting a particular individual and are often based on ease of access.

Convenience Sampling

An example of nonprobability sampling where researchers select participants who are readily available (e.g., students in a classroom).

Stratified Random Sampling

The population is divided into subgroups (strata), and an equal-sized random sample is selected from each subgroup.

Proportionate Stratified Random Sampling

The population is divided into subgroups, but random samples are selected from each group in proportion to their representation within the population.

Internal Validity

Refers to whether a study produces a single, unambiguous explanation for the relationship between two variables.

Confounding Variables

Extraneous variables that systematically vary along with the independent variable, providing an alternative explanation for the observed relationship.

PET Confounding Variables

The three main categories of confounding variables are Participant variables (individual differences), Environmental confounds, and Time-related confounds.

Assignment Bias

An example of a participant variable confound where participants in different treatment conditions are inherently different in a way that could affect the outcome.

Internal Validity vs External Validity

Internal validity concerns the extent to which a study can establish a clear cause-and-effect relationship between variables.

External validity

Concerns the extent to which the results of a study can be generalized to other populations, settings, times, or measures.

Descriptive research

The goal is to measure variables as they exist naturally within a group and simply describe them, without examining relationships between variables or attempting to establish causality.

Example of descriptive research finding

Stating the median household income in a specific county based on recent data.

Correlational study

Examines the relationship or association between two or more variables that are measured but not manipulated by the researcher.

Limitation of correlational research

It cannot establish causality; just because two variables are related does not mean that one causes the other.

Challenges of studying entire populations

Studying entire populations is often too expensive and impractical due to the large number of individuals involved and the resources required.

Importance of representative sample

It increases the likelihood that the findings obtained from studying the sample can be generalized to the broader population.

Simple random sampling

Each individual has an equal and independent chance of being chosen.

Convenience sampling

Researchers select participants who are readily available, such as students in a classroom.

Proportionate stratified random sampling

Random samples are selected from each group in proportion to their representation within the population.

Categories of confounding variables

Participant variables (individual differences), Environmental confounds, and Time-related confounds.

Participant variable confound

Assignment bias, where participants in different treatment conditions are inherently different in a way that could affect the outcome.

Internal validity

The extent to which a study can establish a clear cause-and-effect relationship between variables, providing a single, unambiguous explanation for the findings within the study itself.

External validity

The extent to which the results of a study can be generalized to other populations, settings, times, or measures.

Descriptive research

Research that aims to measure variables as they exist naturally within a group and simply describe them, without examining relationships between variables or attempting to establish causality.

Correlational study

A study that examines the relationship or association between two or more variables that are measured but not manipulated by the researcher.

Causality

The relationship between cause and effect, which correlational research cannot establish.

Third-variable problem

A limitation in correlational research where an unmeasured variable may influence both variables being studied.

Directionality problem

A challenge in correlational research where the direction of the relationship between two variables may be the reverse of what is assumed.

Population

The entire set of individuals or items of interest to a researcher.

Sample

A subset of individuals or items selected from the population to participate in a research study.

Probability Sampling

Sampling techniques in which every member of the population has a known probability of being selected for the sample, and a random process is used for selection.

Nonprobability Sampling

Sampling techniques in which the probability of selecting any particular member of the population is unknown, often based on convenience or availability.

Simple Random Sampling

A probability sampling method in which every individual in the population has an equal and independent chance of being selected.

Stratified Random Sampling

A probability sampling method in which the population is divided into subgroups (strata), and a random sample is taken from each stratum.

Proportionate Stratified Random Sampling

A probability sampling method in which the population is divided into subgroups, and random samples are selected from each group in proportion to their representation in the population.

Cluster Sampling

A probability sampling method in which pre-existing groups (clusters) within the population are randomly selected, and then either all individuals within the selected clusters are included in the sample, or a random sample is drawn from each selected cluster.

Convenience Sampling

A nonprobability sampling method in which participants are selected because they are easily accessible to the researcher.

Quota Sampling

A nonprobability sampling method in which researchers attempt to obtain specific proportions of participants in their sample to match the proportions found in the population, but use non-random methods for selection within those quotas.

Internal Validity

The extent to which a research study produces a single, unambiguous explanation for the relationship between two variables.

External Validity

The extent to which the results of a research study can be generalized to other populations, settings, times, or measures.

Confounding Variable

An extraneous variable that systematically varies along with the independent variable, providing an alternative explanation for the observed relationship and threatening internal validity.

Participant Variable

Individual differences among participants that can become confounding variables if not controlled for.

Environmental Confound

Aspects of the study's environment that differ systematically across treatment conditions and can provide an alternative explanation for the results.

Time-Related Confound

Factors that change over time during a study (especially in studies with repeated measures) that can affect participants' responses and confound the results.

Descriptive Research

Research methods focused on measuring and describing variables as they exist naturally within a group, without manipulating variables or determining relationships.

Naturalistic Observation

A descriptive research method in which behavior is observed in its natural setting without any attempt by the researcher to manipulate or control the situation.

Participant Observation

A descriptive research method in which the researcher becomes a participant in the group or situation being observed.

Contrived Observation (Structured Observation)

A descriptive research method in which the researcher creates a specific setting or situation to facilitate the occurrence of certain behaviors that can then be observed.

Survey Research

A descriptive research method that uses questionnaires or interviews to gather information about the attitudes, beliefs, opinions, or behaviors of a group of individuals.

Case Study

An in-depth and detailed examination of a single individual, event, or situation.

Correlational Research

A non-experimental research method that examines the relationship or association between two or more variables.

Directionality Problem

In correlational research, the difficulty in determining whether variable X causes variable Y or vice versa.

Third-Variable Problem

In correlational research, the possibility that an unmeasured third variable is responsible for the observed relationship between two other variables.

Coefficient of Determination (r²)

In correlational research, the proportion of variance in one variable that is explained by the variance in the other variable, indicating the strength of the relationship.