New YorkNew York High School Statistics Curriculum
Video lessons and practice for every high school Statistics topic. Aligned to NYS Next Generation Mathematics Learning Standards for New York students.
New York High School Statistics Curriculum | StudyPugHelp
ID | Math Standard Description | 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 New York
New York high school Statistics gives students the tools to collect, analyze, and interpret data. The course follows the NYS Next Generation Mathematics Learning Standards and prepares students for Regents Exams and college-level quantitative reasoning.
Data Analysis and Distributions
Students begin by representing data using dot plots, histograms, and box plots. They compare data sets by examining center (mean and median) and spread (interquartile range and standard deviation). Outliers and their effects on distributions are also explored. StudyPug has video lessons for every one of these topics, so New York students can revisit any concept after class.
Correlation, Scatter Plots, and Linear Models
Students learn to plot two quantitative variables on a scatter plot, compute the correlation coefficient using technology, and fit a linear model to the data. A key standard in this unit is distinguishing between correlation and causation — a concept that appears frequently on assessments and in everyday reasoning.
Normal Distributions and Population Estimates
High school Statistics students use the mean and standard deviation to fit data to a normal distribution and estimate population percentages. They use calculators, spreadsheets, and tables to estimate areas under the normal curve, following NYS Next Generation Mathematics Learning Standards expectations.
Statistical Inference and Sampling
Students learn that statistics is a process for making inferences about populations based on random samples. This unit covers sample surveys, experiments, and observational studies, and explains how randomization relates to each. Students develop margins of error through simulation and evaluate reports based on data.
Probability and Independent Events
The probability strand covers independence, conditional probability, the Addition Rule, and the general Multiplication Rule. Students construct and interpret two-way frequency tables as sample spaces to decide if events are independent and to approximate conditional probabilities.
- P(A and B) = P(A) × P(B) for independent events
- Conditional probability: P(A|B) = P(A and B) / P(B)
- Addition Rule: P(A or B) = P(A) + P(B) − P(A and B)
- Permutations and combinations for compound event probabilities
Random Variables and Expected Value
Students define random variables, graph probability distributions, and calculate expected values. They develop distributions using both theoretical and empirical probabilities. These skills connect directly to real-world decision-making, such as product testing, medical testing, and analyzing game strategies.
How StudyPug Supports New York Statistics Students
StudyPug provides video lessons and practice problems for every topic in the New York high school Statistics course. Each lesson is 5–15 minutes long and can be paused, rewound, and replayed. Students can search by NYS standard, follow along with worked examples, and then test their understanding with practice problems — all aligned to what New York schools teach.