Rhode IslandRhode Island High School Statistics Curriculum
Video lessons and practice for every high school Statistics topic. Aligned to Rhode Island Math Standards so students can keep up, catch up, or get ahead.
Rhode Island High School Statistics Curriculum | StudyPugHelp
ID | Standard | 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). |
High School Statistics in Rhode Island
Rhode Island high school Statistics follows the Rhode Island Math Standards and builds the skills students need to analyze data, understand probability, and draw conclusions from real-world information. StudyPug covers every topic in the course with clear video lessons and targeted practice problems.
Data Analysis and Distributions
Students learn to represent data using dot plots, histograms, and box plots on the real number line. The course covers how to compare data sets using measures of center — mean and median — and spread, including interquartile range and standard deviation. Students interpret differences in shape, center, and spread and identify the effects of outliers on a data set.
- Dot plots, histograms, and box plots
- Mean, median, interquartile range, and standard deviation
- Normal distributions and estimating population percentages
- Two-way frequency tables with joint, marginal, and conditional relative frequencies
Scatter Plots, Correlation, and Causation
Students represent two quantitative variables on scatter plots and describe relationships between them. They compute and interpret the correlation coefficient of a linear fit using technology, and learn to distinguish clearly between correlation and causation — a critical skill for evaluating real-world claims.
Statistical Inference and Study Design
Students explore statistics as a process for drawing conclusions about populations from random samples. Topics include the differences among sample surveys, experiments, and observational studies, as well as the role randomization plays in each. Students use simulation models to develop margins of error and evaluate the significance of experimental results.
- Sample surveys, experiments, and observational studies
- Margin of error through simulation
- Comparing two treatments using randomized experiments
- Evaluating reports based on data
Probability
The probability unit covers independent events, conditional probability, the Addition Rule, and the general Multiplication Rule. Students construct and interpret two-way frequency tables as sample spaces and use permutations and combinations to compute probabilities of compound events.
Random Variables and Expected Value
Students define random variables, graph probability distributions, and calculate expected values. They develop probability distributions using both theoretical and empirical approaches and apply expected value to weigh outcomes of decisions, evaluate strategies, and analyze real-world situations such as medical testing and game decisions.