Introduction to Social Research

A research method that focuses on understanding the experiences and meanings of individuals.

A research method that uses numbers and statistics to analyze data.

The question or issue you want to investigate in your research.

A testable statement about a relationship between variables.

Participants must know about the research and agree to participate voluntarily.

Protecting the privacy of research participants.

Accuracy of research measures in measuring what they are intended to.

Consistency of research results.

A hypothesis that predicts a relationship or effect exists.

The plan for conducting research, choosing the right methods based on the research question(s).

Selecting participants from a larger group for research.

A sampling method where each person has an equal chance of being chosen.

Gathering information using methods like surveys, interviews, or observation.

The number of participants needed for a study to be statistically valid.

After collecting data, it gets examined to find patterns and meaning. This can involve either coding textual data for themes (qualitative) or using statistical techniques like t-tests (quantitative).

A way to analyze data that involves looking for themes, patterns, and insights within textual data. For example, reading interview transcripts for recurring ideas.

Analyzing numbers and data using statistical methods like averages, correlations, or t-tests.

Making sense of the analyzed data to draw meaningful conclusions that address the research problem.

A written document that presents the findings of a research study. It covers the study's background, methodology, results, and conclusions.

A set of ideas used to explain how things in the world are related.

It helps answer crucial questions about how you'll conduct your study, such as the methods used to gather data, participant selection, data analysis, and ensuring study validity and reliability.

Used to investigate little-known or new phenomena. It aims to gain initial insights and understanding and lays the groundwork for further research.

To delve into new or poorly understood topics, establish a foundation for further investigation, and generate hypotheses for future research.

Categorizations of research approaches based on their purpose and methodologies. Common types include exploratory, descriptive, explanatory, and experimental.

Used to describe characteristics of a population or phenomenon. It aims to systematically gather information about a topic.

Used to explain relationships between variables or the causes of phenomena. It aims to establish causal connections.

Used to test cause-and-effect relationships. It involves manipulating an independent variable to observe its impact on a dependent variable.

Research approaches that focus on understanding experiences and meanings through open-ended questions and flexible data collection methods, like interviews or focus groups.

Research that aims to describe characteristics or behaviors of a population or phenomenon, answering 'what' questions but not 'why'.

Structured questionnaires used to gather information from a large sample about their opinions, behaviors, or experiences.

Research that seeks to identify causal relationships between variables, explaining why something happens.

The assurance that the observed effects in a study are genuinely due to the manipulated variable, not other factors.

The extent to which the findings of a study can be generalized to other populations or settings.

The extent to which the findings of a study can be applied to a larger population or different settings.

A research approach where theories emerge from data analysis rather than being predetermined.

Using empirical evidence to evaluate the validity of theoretical assumptions, leading to either support or refutation.

Classifies data into categories without an order or ranking (e.g., gender, race).

Organizes data into categories with a defined order but the distances between categories aren't precise (e.g., social class, ranks).

Data categories are ordered with equal distances between them, but there's no true zero point (e.g., temperature in Celsius).

Has all the characteristics of an interval scale and includes a true zero point (e.g., income, age).