Real numbers, expressions and properties
8 lessonsSets of numbers and the properties of the real numbers that justify every algebraic move, plus estimating with quantities.
Linear inequalities in one and two variables
12 lessonsSolving multi-step and compound inequalities, writing their solution sets, and graphing inequalities and their overlaps in the plane.
Functions: notation, domain, range, graphs and linear models
13 lessonsUsing function notation in context, reading domain, range and end behavior from graphs, measuring average rate of change, and linear functions as models.
Piecewise and absolute value functions
8 lessonsFunctions defined by pieces, the absolute value function, and solving absolute value equations and inequalities as distance.
Arithmetic and geometric sequences
6 lessonsSequences as functions on the counting numbers, with explicit and recursive rules for adding and multiplying patterns.
Exponential functions and choosing a model
12 lessonsExponential growth and decay, their graphs, and choosing, building and interpreting linear and exponential models.
Polynomials and their operations
5 lessonsPolynomials as sums of monomials, and adding, subtracting and multiplying them, including the special products.
Factoring
5 lessonsUndoing multiplication by factoring trinomials, grouping, special patterns, and choosing a strategy to factor completely.
Quadratic functions and their graphs
10 lessonsThe parabola, its vertex, axis and zeros, and the features of any graph read off a quadratic, with quadratics in context.
Radicals
3 lessonsSimplifying square roots and computing with radicals, ready for the radical answers of the quadratic formula.
Solving quadratic equations
12 lessonsSolving quadratics by factoring, square roots, completing the square and the quadratic formula, and choosing the method.
One-variable statistics
7 lessonsDescribing a distribution with percentiles, outliers and the standard deviation, and what rescaling data does to them.
Two-variable statistics
11 lessonsFitting and judging a line for paired data with residuals and correlation, and why correlation is not causation.