Statistics Concept Guides
The core ideas you need to read and report results correctly, each with worked numeric examples you can reproduce in the calculators.
Standard Deviation: Sample (n−1) vs Population (n)
Why does the sample standard deviation divide by n−1? Bessel's correction, Excel STDEV.S vs STDEV.P, and a small worked example by hand.
G02Quartiles, IQR and Outliers: Why Methods Give Different Values
Why Excel QUARTILE.INC, QUARTILE.EXC and Tukey's hinges differ, plus the IQR, the 1.5×IQR outlier rule and box plots.
G03Normal Distribution and z-Scores: Cumulative Probability and Top-x% Cutoffs
The normal distribution, z-scores, the 68–95–99.7 rule, cumulative probabilities and finding a top-10% cutoff score.
G04Interpreting p-Values: The Definition and 5 Common Misconceptions
What a p-value really is, five common misconceptions, significance levels, effect sizes and one- vs two-sided tests.
G05What a 95% Confidence Interval Really Means, and How to Compute It
How to read a 95% confidence interval correctly, z vs t, worked mean and proportion examples, and Wald vs Wilson.
G06Survey Sample Size: Choosing It from Margin of Error and Confidence Level
n = z²·p(1−p)/E², why p = 0.5, finite population correction, sample sizes by confidence and margin, and response rates.
G07Which Statistical Test Should You Use? A Practical Selection Guide
Choose a t-test, chi-square test, correlation or nonparametric test by data type, number of groups and pairing.
G08Correlation vs Regression: Pearson r, Spearman ρ and Interpreting the Slope
Pearson vs Spearman, r², reading a regression slope, correlation vs causation and outliers, with a worked example.