New JerseyNew Jersey High School Statistics Curriculum
Video lessons and practice for every high school Statistics topic. Aligned to NJ Student Learning Standards for Math so New Jersey students stay on track.
New Jersey 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 New Jersey
New Jersey high school Statistics covers a wide range of topics aligned to the NJ Student Learning Standards for Math. Students learn to analyze data, understand probability, make inferences from samples, and work with random variables. These skills are essential for college readiness and are tested in courses like AP Statistics and the SAT.
Data Analysis and Distributions
Students begin by representing data using dot plots, histograms, and box plots. They compare data sets using measures of center (mean and median) and spread (interquartile range and standard deviation). Outliers and their effects on distributions are examined, and students learn to fit data to a normal distribution and estimate population percentages using the normal curve.
- Dot plots, histograms, and box plots
- Mean, median, IQR, and standard deviation
- Normal distribution and population estimates
- Two-way frequency tables and relative frequencies
Linear Regression and Correlation
Students represent two-variable data on scatter plots, compute correlation coefficients using technology, and interpret the strength of a linear relationship. A key concept at this level is understanding the difference between correlation and causation — an important critical thinking skill for evaluating real-world data claims.
Statistical Inference and Sampling
Statistics as a process for making inferences is a central theme. Students learn to distinguish between sample surveys, experiments, and observational studies. They use simulation to estimate margins of error, compare two treatments from randomized experiments, and evaluate reports based on data. Randomization and its role in valid inference is emphasized throughout.
- Sample surveys vs. experiments vs. observational studies
- Margin of error through simulation
- Comparing two treatments with randomized experiments
- Evaluating data-based reports
Probability
Students develop a thorough understanding of probability, including independent events, conditional probability, and the rules that govern them. The Addition Rule and Multiplication Rule are applied in context, and students use permutations and combinations to compute probabilities of compound events.
- Independent events and conditional probability
- Two-way tables as sample spaces
- 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
Students define random variables, graph probability distributions, and calculate expected values. They develop probability distributions using both theoretical probabilities and empirical data. Expected value is applied to real-world decision-making — from product testing to medical decisions — giving students practical tools for analyzing risk and fairness.