District of ColumbiaDC High School Statistics Curriculum
Video lessons and practice for every high school Statistics topic. Aligned to what Washington DC schools teach. Get help with data, probability, and more.
DC 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 Washington DC
Washington DC high school Statistics courses prepare students to work with real data, understand probability, and draw conclusions from evidence. StudyPug covers every major topic in the DC Statistics curriculum, from dot plots and histograms to permutations and expected value.
Data Analysis and Distributions
Students start by learning to represent data using dot plots, histograms, and box plots. They compare data sets using measures of center — mean and median — and measures of spread like interquartile range and standard deviation. StudyPug's video lessons walk through each concept step by step, so students can follow along and practice immediately.
- Represent data with dot plots, histograms, and box plots
- Compare center and spread across two or more data sets
- Identify and account for outliers in data distributions
- Fit data to a normal distribution and estimate population percentages
- Use calculators and tables to estimate areas under the normal curve
Bivariate Data and Correlation
High school Statistics students in DC learn to analyze relationships between two variables. They create scatter plots, compute correlation coefficients, and distinguish between correlation and causation. These skills are foundational for AP Statistics and college-level data analysis.
- Represent two-variable data on scatter plots
- Compute and interpret correlation coefficients using technology
- Distinguish between correlation and causation
- Summarize categorical data in two-way frequency tables
- Interpret joint, marginal, and conditional relative frequencies
Statistical Inference and Sampling
Students learn how statistics is used to make inferences about populations from sample data. Topics include random sampling, margin of error, randomized experiments, and evaluating data reports. StudyPug explains each concept clearly with worked examples grounded in real contexts.
- Understand sampling as a basis for population inference
- Use simulation to test whether a model fits observed data
- Distinguish sample surveys, experiments, and observational studies
- Estimate population means and proportions with margin of error
- Evaluate the quality and validity of data-based reports
Probability
The probability unit covers independence, conditional probability, addition and multiplication rules, and counting methods. Students apply these ideas to everyday situations and build toward formal probability modeling. Every rule is explained with plain language and concrete examples.
- Understand and apply the concept of independent events
- Calculate conditional probabilities using P(A and B)/P(B)
- Construct and interpret two-way frequency tables as sample spaces
- Apply the Addition Rule and general Multiplication Rule
- Use permutations and combinations to find probabilities of compound events
Random Variables and Expected Value
Students define random variables, graph probability distributions, and calculate expected values. They develop distributions from both theoretical and empirical data, and apply expected value to real decisions — from games of chance to medical testing strategies.
- Define random variables and graph probability distributions
- Calculate expected value and interpret it as the mean of a distribution
- Develop theoretical and empirical probability distributions
- Weigh outcomes by assigning probabilities to payoff values
- Analyze decisions and strategies using probability concepts