High Probability and Statistics

Segment One:

• Select an appropriate method to represent data.
• Interpret data distributions represented in various ways.
• Solve real-world problems involving univariate and bivariate categorical data.
• Calculate and compare the appropriate measures of center and measures of variability.
• Construct two-way frequency tables and interpret frequencies in terms of a real-world context.
• Construct and interpret a segmented bar graph.
• Compute the correlation coefficient of a linear model using technology and interpret the strength and direction of the correlation coefficient.
• Fit a linear function to bivariate numerical data that suggests a linear association and interpret the slope and y-intercept of the model.
• Given a scatter plot, assess the fit of a given linear function by plotting and analyzing residuals.
• Explain the difference between correlation and causation.
• Fit an exponential function to bivariate numerical data that suggests an exponential association.

Segment Two:

• Distinguish between a population parameter and a sample statistic.
• Explain how random sampling produces data that is representative of a population.
• Compare and contrast sampling methods.
• Determine the appropriate design, survey, experiment, or observational study, based on the purpose, and compare and contrast surveys, experiments, and observational studies.
• Compare two treatments using data from an experiment in which the treatments are assigned randomly.
• Estimate a population total, mean, or percentage using data from a sample survey.
• Interpret the margin of error of a mean or percentage from a data set and the confidence level corresponding to the margin of error.
• Apply probabilities to make fair decisions.
• Draw inferences about two populations using data and statistical analysis.
• Evaluate reports based on data from diverse media.
• Describe events as subsets of a sample space.
• Calculate the appropriate permutation or combination.
• Calculate the conditional probability of two events and interpret the result in terms of its context.
• Define a random variable for a quantity of interest.
• Develop a probability distribution for a discrete random variable using theoretical and empirical probabilities.
• Given a binomial distribution, calculate and interpret the expected value.
• Solve real-world problems involving geometric distributions.
• Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages.

Besides engaging students in challenging curriculum, the course guides students to reflect on their learning and evaluate their progress through a variety of assessments. Assessments can be in the form of practice lessons, multiple-choice questions, writing assignments, projects, lab activities, research papers, oral assessments, and discussions. This course will use the state-approved grading scale. Each course contains a mandatory final exam or culminating project that will be weighted at 20% of the student’s overall grade.

***Proctored exams can be requested by FLVS at any time and for any reason in an effort to ensure academic integrity. When taking the exam to assess a student’s integrity, the exam must be passed with at least a 59.5% in order to earn credit for the course.

To achieve success, students are expected to submit work in each course weekly. Students can learn at their own pace; however, “any pace” still means that students must make progress in the course every week. To measure learning, students complete self-checks, practice lessons, multiple choice questions, projects, discussion-based assessments, and discussions. Students are expected to maintain regular contact with teachers; the minimum requirement is monthly. When teachers, students, and parents work together, students are successful.