Statistics
This course includes the gathering of data and a variety of sampling techniques, hypothesis testing, frequency distribution, normal distribution, correlation, linear regression, theoretical distributions, and inferential statistics. This course asks students to consider questions such as these: How is data summarized so that it is intelligible? How should statistical data be interpreted? How can we measure the inherent uncertainty built into statistical data? Students will be asked to collect, analyze and interpret real data to answer real questions in their areas of interest.
Students can opt to take this class at the Honors level.
Prerequisites: Integrated Math 3 or Algebra 2 and Geometry
PreCalculus – Functions
In this course, students will take a deeper look at various families of functions: rational, radical, exponential, logarithmic, and polynomial. Students will learn about the ways in which domain, range, continuity, inverses, composition and transformation apply to those functions. Students will also have opportunities to analyze real-world data and generate predictive models. Topics from data science are often included in this course, as well.
Prerequisites: Integrated Math 2 and Integrated Math 3. Offered at the Honors and Standard levels. Honors level requires departmental recommendation.
Integrated Math 3: Algebra, Geometry, and Data Science
Integrated Math 3 students continue to expand their algebraic reasoning and understanding of mathematical models including complex numbers, exponential equations, and polynomials. Students also explore sampling and build upon their knowledge of solid geometry and circle theorems while building connections between all topics covered.
Prerequisites: Integrated Math 2. Offered at the Honors and Standard levels. Honors level requires departmental recommendation.