Quantitative Methods, Statistics, and Research: Design and Interpretation
Research Design
Know quantitative vs. qualitative approaches and mixed methods. Review experimental, quasi-experimental, correlational, survey, and case study designs. Understand validity (internal and external) and reliability. Distinguish population from sample, and know probability vs. non-probability sampling (simple random, stratified, cluster, convenience, purposive).
Statistics
Review measures of central tendency (mean, median, mode) and dispersion (range, variance, standard deviation). Understand normal distribution, z-scores, confidence intervals, hypothesis testing (null vs. alternative, Type I and Type II errors, p-values), and correlation vs. causation. Know when to use t-tests, chi-square, and ANOVA.
Traps
Questions confuse Type I (rejecting a true null) with Type II (failing to reject a false null). They misread correlation as causation, or mistake statistical significance for practical significance. Watch for options confusing standard deviation with standard error.
Rule of Thumb
For any statistic, ask: What is being measured, what is the unit, and what does the number mean in context? Significance tells you about chance, not about importance.
Worked example: A p-value of 0.03 at α = 0.05 means reject the null; it does not mean the effect is large or important.