Course Description
Probability [Competency Based]
In this course, students take a comprehensive and engaging look at the field of probability. They begin by learning the basic terms, types, theories and rules of probability. Next, the course covers random outcomes and normal distributions, as well as binomial probabilities. Finally, students learn about geometric probability, sampling distribution, populations, and the central limit theorem. By the end of this course, students gain a knowledge of and appreciation for the field of probability and its uses in everyday life
Statistics [Competency Based]
Statistics opens students’ eyes to the many uses of statistics in the real world—from sports and the weather to health and politics. Students learn basic concepts, how to use graphs to represent data, and ways to analyze data. They explore statistical relationships, including the use of correlations, residuals and residual plots, and scatter plots. Finally, students learn how to model nonlinear relationships by using exponential and logarithmic functions and how to design a sample to produce the correct type of data (observational or experimental). By the end of this course, students gain a knowledge of and appreciation for the field of statistics and its applications in the real world.
Course Breakdown
Lesson Assessments – 30%
Quizzes – 25%
Review Assignments – 10%
Exams – 35% Collecting and interpreting data
Normal distributions
Scatter plots
Regression
Exponential and logarithmic data
Samples and experimental design
Course Goals
Analyze rules and notation used in probability.
Explore sampling and applications in various populations.
Apply the probability rules to a variety of applications.
Investigate different variables used in probability concepts. Analyze different ways to collect and interpret data.
Apply data distribution to a variety of problems.
Evaluate sampling methods and experimental design to conduct and interpret research.