1.  Data Collection and Analysis, Ch. 1 & 2
   2. Random Variables,  Probability & Independence, Ch. 4
   3. Discrete Random Variables, Binomial Distributions, Ch. 4
   4. Continuous Random Variables, Normal Distribution, Ch. 4
   5. Sampling Distributions, Ch. 5
   6. Central Limit Theorem, Ch. 5
   7. Parameter estimation, Ch. 5
   8. Hypothesis Testing, Ch. 6
   9. Confidence Intervals, Ch. 6
  10. Simple linear regression & Correlation, Ch. 7

Experiments vs. observational studies, controlled,
	randomized, double-blinded studies
Mean, Median, Mode, Quartiles, 5# summary
Stationarity
Moving Averages
Histograms - raw, relative, density, 
	Box-and-whisker-plots, stem-and-leaf
Trimmed, Winsorized means and Resistancy 
Probabilities - Bernoulli-trials & Binomial experiments
Linear transforms: E(aX + b) = a E(X) +b; SD(aX +b) = |a| SD(X)
		   E(X+Y) = E(X) + E(Y)
		   X & Y indep ==> Var(X+Y) = Var(X) + Var(Y)
		   X & Y depend ==> Var(X+Y) contingent upon dependence
Conditional probability (Bayes Rule)
	Statistical independence P(A | B) = P(A)
Poisson Distribution (approx. to Binomial)
Normal distribution (approx. to Binomial/Poisson).