Core answer: quartiles split ranked data at 25/50/75%, IQR=Q3−Q1, and values outside [Q1−1.5×IQR, Q3+1.5×IQR] are outliers; linear regression ŷ=a+bx fits by least squares with r² as explained variance; independent event probabilities multiply, mutually exclusive add; scientific notation writes a×10ⁿ with 1≤|a|<10.

Quartiles and box plots

After sorting: Q1 at 25%, median at 50%, Q3 at 75% (linear interpolation, matching Excel PERCENTILE.INC). Box plot five numbers: min, Q1, median, Q3, max, with outliers drawn as points. Fences: Q1−1.5×IQR and Q3+1.5×IQR; beyond 3×IQR is extreme.

Least-squares regression

Fit ŷ=a+bx:

  • Slope b = Σ(x−x̄)(y−ȳ) ÷ Σ(x−x̄)²
  • Intercept a = ȳ − b·x̄
  • r² = share of y’s variance explained by x
Fit
<0.3weak
0.3-0.7moderate
>0.7strong

Three rules of probability

  1. Range: [0,1] — 0 impossible, 1 certain
  2. Independent → multiply: two heads in a row = 0.5×0.5 = 0.25
  3. Mutually exclusive → add: die shows 1 or 2 = 1/6+1/6 = 1/3

At least once goes through the complement: 10 draws at 5% each → 1−0.95¹⁰ = 40.1%, not 50%.

Sci notation and rounding

Scientific notation a×10ⁿ (1≤|a|<10): 299792458 m/s = 3.00×10⁸ (3 sig figs).

Rule2.5 →3.5 →Use
Half-up34everyday
Banker’s (half-even)24finance/stats de-biasing
Floor23conservative estimates

Half-even pulls .5 to the nearest even digit, so long sums avoid systematic upward drift.

Example: salary outlier detection

Nine salaries (k): 6, 7, 8, 8, 9, 10, 11, 12, 45. Q1=7.5, Q3=11.5, IQR=4 → upper fence 17.5 → 45 flagged (the boss). Median 9 tells the truth; mean 12.9 is dragged up — the classic “average wage” illusion.

Example: area-to-price regression

Five homes: 60/80/90/110/130㎡, prices 180/230/260/310/350. Least squares gives ŷ=35+2.43x with r²≈0.99. Prediction at 100㎡ → ~278. High r² is not causation — area proxies location, and extrapolating to a 200㎡ villa breaks the model.

Common pitfalls

  • “The mean is typical”: right-skewed income data demands the median — the quartile tool prints all five numbers plus the box.
  • “High r² means causation”: ice cream vs drowning correlates strongly; the driver is summer. Correlation ≠ causation.
  • “Multiplication always applies”: drawing without replacement breaks independence — the second draw is conditional.
  • “0.5 must round up”: banker’s rounding sends 2.5→2 and 3.5→4, erasing bias in financial ledgers.