Probability for things you measure.
Heights, waiting times, temperatures. Quantities you measure rather than count have infinitely many possible values, so a probability table cannot describe them. Instead probability becomes area under a curve, and integration does the work. This leads to the normal distribution, the most widely used model in all of statistics.
Lesson 1
General Continuous Random Variables
Probabilities from histograms, probability density functions and validity, probabilities from graphs and rules including piecewise definitions, and cumulative distribution functions in both directions. Twenty practice questions, ten harder ones, and a ClassPad guide.
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Measures of Centre & Spread
Mean by integration, median, quartiles and percentiles, variance and standard deviation, and the effect of linear changes of scale and origin. Twenty practice questions, ten harder ones, and a ClassPad guide.
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Uniform & Triangular Distributions
The uniform distribution with its standard formulas, symmetric and asymmetric triangular distributions, probabilities by geometry, and these distributions feeding binomial questions. Twenty practice questions, ten harder ones, and a ClassPad guide.
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The Normal Distribution
The bell curve, the meaning of the mean and standard deviation, the 68-95-99.7 rule, the standard normal and z-scores, and probabilities and quantiles with technology. Twenty practice questions, ten harder ones, and a ClassPad guide.
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