Lesson 1 – Introduction to Quantitative Research (Vocabulary Review)

Twenty-three vocabulary flashcards summarizing key terms, characteristics, advantages, disadvantages, and designs associated with quantitative research from Lesson 1.

Quantitative Research

A formal, objective, and systematic investigation that gathers numerical data and applies statistical analysis to understand observable phenomena.

Qualitative Research

A research method that explores and describes phenomena narratively using words, images, or transcripts from small, non-generalizable samples.

Phenomenon

Any existing or observable fact, event, or situation that a researcher aims to study or understand further.

Numerical Data

Information expressed in numbers that can be measured, counted, and subjected to statistical analysis.

Likert Scale

A rating scale that converts qualitative judgments (e.g., taste, agreement) into numerical values to allow statistical treatment.

Large Sample Size

A characteristic of quantitative studies in which many participants are included to obtain meaningful and generalizable statistical results.

Objectivity

Freedom from researcher bias; data collection and analysis are based on measurable facts rather than personal intuition or guesses.

Concise Visual Presentation

The use of graphs, charts, and tables to clearly display numerical findings for easier interpretation.

Faster Data Analysis

The reduced time required to interpret results when statistical software and mathematical procedures are applied to numerical data.

Generalized Data

Findings from a sample that can be applied to an entire population when sampling is sufficiently large and random.

Fast and Easy Data Collection

The ability to gather information quickly with standardized instruments, especially from large groups at once.

Reliable Data

Credible information obtained and analyzed objectively, serving as a sound basis for policy and decision making.

High Replicability

The capacity of a study to be repeated by other researchers to verify findings, enhancing validity.

Advantages of Quantitative Research

Strengths include objectivity, predictable outcomes from numerical data, generalizability, clear cause-and-effect testing, quick data gathering and analysis, replicability, and demonstrable validity and reliability.

Disadvantages of Quantitative Research

Weaknesses such as limited depth, inadequate explanation of human experiences, inability to capture feelings, rigid design, restricted participant responses, potential inaccurate answers, and higher cost for large samples.

Descriptive Research Design

A non-experimental approach that observes and reports characteristics of a phenomenon without manipulating variables or starting with a hypothesis.

Correlational Research Design

A design that measures the relationship or association between two or more variables without inferring cause and effect.

Ex Post Facto Design

Research that investigates possible relationships between past events and present conditions without manipulating variables, literally meaning ‘after the fact.’

Quasi-Experimental Design

A study that seeks cause-and-effect relationships without random assignment; existing groups serve as experimental and control units, reducing internal validity compared to true experiments.

Experimental Design

A rigorous method that uses random assignment and manipulation of independent variables to establish conclusive cause-and-effect relationships.

Pearson’s r

A statistical measure that indicates the strength and direction of a linear correlation between two continuous variables.

t-test

An inferential statistic used to determine whether there is a significant difference between the means of two groups.

Analysis of Variance (ANOVA)

A statistical technique that compares the means of three or more groups to see if at least one differs significantly from the others.