FloridaFlorida High School Statistics Curriculum
Video lessons and practice for every high school Statistics topic. Aligned to Florida's B.E.S.T. Standards for Mathematics so students can keep up with class or get ahead.
Florida High School Statistics Curriculum | StudyPugHelp
FL Standard | Shortened Benchmark | StudyPug Topic |
|---|---|---|
CC.HSS.ID.A.1 | Represent data with plots on the real number line (dot plots, histograms, and box plots). |
CC.HSS.ID.A.2 | Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets. |
CC.HSS.ID.A.3 | Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers). |
CC.HSS.ID.A.4 | Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve. |
CC.HSS.ID.B.5 | Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data. |
CC.HSS.ID.B.6 | Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. |
CC.HSS.IC.A.1 | Understand statistics as a process for making inferences about population parameters based on a random sample from that population. |
CC.HSS.IC.A.2 | Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation. |
CC.HSS.IC.B.3 | Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each. |
CC.HSS.IC.B.4 | Use data from a sample survey to estimate a population mean or proportion; develop a margin of error through the use of simulation models for random sampling. |
CC.HSS.IC.B.5 | Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant. |
CC.HSS.IC.B.6 | Evaluate reports based on data. |
CC.HSS.CP.A.2 | Understand that two events A and B are independent if the probability of A and B occurring together is the product of their probabilities, and use this characterization to determine if they are independent. |
CC.HSS.CP.A.3 | Understand the conditional probability of A given B as P(A and B)/P(B), and interpret independence of A and B as saying that the conditional probability of A given B is the same as the probability of A, and the conditional probability of B given A is the same as the probability of B. |
CC.HSS.CP.A.5 | Recognize and explain the concepts of conditional probability and independence in everyday language and everyday situations. |
CC.HSS.CP.B.7 | Apply the Addition Rule, P(A or B) = P(A) + P(B) - P(A and B), and interpret the answer in terms of the model. |
CC.HSS.CP.B.9 | Use permutations and combinations to compute probabilities of compound events and solve problems. |
CC.HSS.MD.A.1 | Define a random variable for a quantity of interest by assigning a numerical value to each event in a sample space; graph the corresponding probability distribution using the same graphical displays as for data distributions. |
CC.HSS.MD.A.2 | Calculate the expected value of a random variable; interpret it as the mean of the probability distribution. |
CC.HSS.MD.A.3 | Develop a probability distribution for a random variable defined for a sample space in which theoretical probabilities can be calculated; find the expected value. |
CC.HSS.MD.B.7 | Analyze decisions and strategies using probability concepts (e.g., product testing, medical testing, pulling a hockey goalie at the end of a game). |
Florida High School Statistics: What Students Learn
Florida high school Statistics is built around three major areas: data analysis, probability, and statistical inference. Each unit aligns to Florida's B.E.S.T. Standards for Mathematics, preparing students for college-level coursework and real-world data reasoning.
Data Analysis and Distributions
Students start by representing data visually — using dot plots, histograms, and box plots on the real number line. From there, they compare data sets by examining center (mean and median) and spread (interquartile range and standard deviation). A key focus is the normal distribution: students learn to use the mean and standard deviation to estimate population percentages and find areas under the normal curve using calculators, spreadsheets, and tables.
- Dot plots, histograms, and box plots
- Mean, median, IQR, and standard deviation
- Normal distribution and population estimates
- Two-way frequency tables with joint, marginal, and conditional relative frequencies
Scatter Plots, Correlation, and Regression
Students learn to represent two quantitative variables on a scatter plot and describe relationships between them. They compute and interpret the correlation coefficient of a linear fit using technology, and — critically — they learn to distinguish between correlation and causation, a concept tested in many college assessments.
- Scatter plots and linear relationships
- Correlation coefficient using technology
- Correlation vs. causation
Statistical Inference and Study Design
This unit introduces statistics as a process for making inferences about populations from random samples. Students compare sample surveys, experiments, and observational studies, and explore how randomization affects each. They estimate population means and proportions, develop margins of error through simulation, and evaluate real-world data reports.
- Random sampling and population inference
- Sample surveys, experiments, and observational studies
- Margin of error and simulation models
- Evaluating reports based on data
Probability
Students develop a thorough understanding of probability, including independent events, conditional probability, the Addition Rule, and the general Multiplication Rule. They work with two-way frequency tables as sample spaces and apply permutations and combinations to solve compound probability problems.
- Independent events and conditional probability
- Addition Rule: P(A or B) = P(A) + P(B) − P(A and B)
- Multiplication Rule: P(A and B) = P(A)P(B|A)
- Permutations and combinations
Random Variables and Expected Value
In the final unit, students define random variables and graph probability distributions. They calculate expected value — both from theoretical models and empirical data — and use expected values to weigh decisions, assess fairness, and analyze real-world strategies like medical testing or game theory scenarios.
- Random variables and probability distributions
- Expected value from theoretical and empirical distributions
- Using probability to make fair decisions
- Analyzing decisions and strategies with probability