In-Depth Notes on Quantitative Research

Introduction to Research

• Definition of Research:
  • Systematic investigation into materials and sources to establish facts and reach conclusions (English Oxford Dictionary).
  • Goals include obtaining information and uncovering truth.

Clinical Research

• Focuses on:
  • Clinical conditions.
  • Improving methods of practice.
  • Knowledge Translation (KT).

The Research Trinity

• Components:
  • Design
  • Measurement
  • Analysis

Importance of Research

• Reboundability: Emphasizes evidence-based approaches to clinical practice.
• Vaccine Controversies:
  • Early reports linking MMR vaccine and autism led to significant public concern.
  • Study summarized included 12 children with chronic gastrointestinal issues and developmental regression.
  • Findings indicated gastrointestinal disease associated with developmental regression but lack of direct correlation with vaccines.

Research Design and Statistics

• Statistics:
  • Procedures for analyzing research data.
  • Collect empirical information through observation and measurement.
• importance in drawing valid conclusions from research.

Population vs Sample

• Population: Total number of cases/items of interest; for example:
  • All university students in Canada.
  • All Canadians over 65.
• Parameters: Numbers characterizing the population (Greek symbols).

Sample Characteristics

• Sample: A subset of the population intended to represent it.
  • E.g., 50 undergraduate students at the University of Guelph from a larger population of 1,440,094 students.
  • Issues with Sampling: Difficulty in ensuring the sample is representative due to random selection challenges.

Inductive vs Deductive Reasoning in Research

• Inductive Reasoning: Drawing general conclusions from specific observations.
• Deductive Reasoning: Starting with general principles and deducing specific outcomes.

The Scientific Method

• Key Steps:[1]. Make an observation
  • [2]. Formulate a question
  • [3]. Design an experiment
  • [4]. Execute the experiment
  • [5]. Analyze the results
  • [6]. Draw conclusions
• Key Elements:
  • Skepticism, objectivity, open-mindedness, and empirical evidence.

Types of Research

• Quantitative Research:
  • Measurement of outcomes using numerical data.
  • Apply statistical procedures for analysis.
• Qualitative Research:
  • Deriving conclusions from open-ended responses; NOT applying numerical descriptions.

Variables and Data

• Variable: Characteristic or condition that changes; can have different values.
• Datatype:
  • Data (plural) are collection of values;
  • Data set includes all data points;
  • Datum (singular) is a single measurement/score.

Descriptive vs Inferential Statistics

• Descriptive Statistics: Procedures to summarize, organize, and simplify data.
• Inferential Statistics: Techniques for studying samples to make generalizations about the larger population.
• Sampling Error: Discrepancies between sample statistics and the population parameters.

Measurement Precision and Scale

• Precision: Refers to the exactness of measurement (e.g., testing instruments).

Measurement Scales

• Nominal Scale: Classification of responses; does not measure amount/value (e.g., gender).
• Ordinal Scale: Categorical scale with a natural order (e.g., income level).
• Interval Scale: Describes actual quantity with equal distances between scores (e.g., temperature).
• Ratio Scale: Represents the true amount; has true zero (e.g., height, weight).

Example of a Research Study Design

• Dependent Variable (DV): Outcome being measured (e.g., test scores).
• Independent Variable (IV): Factor influencing the outcome (e.g., study methods).
• Correlational Research: Examines relationships between variables, using scatterplots and summary statistics to interpret findings.