44. Statistical Analysis in Quantitative Research

About this lesson

Welcome to Module 3.14, your concise guide to the fundamentals of statistical analysis in quantitative research. Whether you're conducting a study or interpreting healthcare literature, understanding basic statistics is essential to evaluating evidence and drawing accurate conclusions.

What You’ll Learn

• How to use descriptive statistics to summarize and visualize data
• The basics of inferential statistics: hypothesis testing, p-values, confidence intervals, and errors
• Common statistical tests used in healthcare research: t-tests, ANOVA, chi-square, correlation, regression
• How to select appropriate statistical tools based on variable types and study design

These fundamentals provide the foundation for conducting reliable, valid, and meaningful statistical analyses in health-related research, and for interpreting results presented in clinical studies, reports, and academic publications.

Topics Covered

• Central Tendency (Mean, Median, Mode)
• Measures of Dispersion (Standard Deviation, Range, Variance)
• P-values and Significance Thresholds
• Confidence Intervals & Hypothesis Testing
• When to Use t-tests, ANOVA, Chi-Square, Correlation, and Regression
• Avoiding Type I & Type II Errors

Perfect For

• Healthcare professionals and clinical researchers
• Public health analysts and policy evaluators
• Students in biostatistics, epidemiology, or research methods
• Anyone needing a strong foundation in research statistics

Learn how to turn raw data into clear, actionable insights that drive evidence-based healthcare.

Lesson notes

Full written notes for this lesson are in production. Until they publish, watch the video above and use the summary on this page as your study guide.