ColoradoColorado High School Statistics Curriculum
Video lessons and practice for every high school Statistics topic. Aligned to Colorado Academic Standards Math so students can keep up with class or get ahead.
Colorado 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 Topics in Colorado
Colorado high school Statistics follows the Colorado Academic Standards Math, covering everything from data visualization to advanced probability. StudyPug breaks each standard into clear video lessons so students can move through topics at their own pace.
Data Analysis and Distributions
Students learn to represent 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), and learn how outliers affect their interpretations. The normal distribution is introduced, with practice using calculators and tables to estimate areas under the normal curve.
Scatter Plots, Correlation, and Causation
Students represent two quantitative variables on scatter plots and use technology to compute the correlation coefficient. A key skill at this level is distinguishing correlation from causation — an important concept for reading real-world data reports critically.
Statistical Inference and Sampling
This unit introduces statistics as a process for making inferences about populations from random samples. Students study the differences among sample surveys, experiments, and observational studies, and use simulation models to develop margins of error and evaluate whether differences between treatments are significant.
Probability Foundations
Students work with independence, conditional probability, the Addition Rule, and the general Multiplication Rule. Two-way frequency tables serve as sample spaces for calculating and interpreting joint, marginal, and conditional relative frequencies. Permutations and combinations are used to compute 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 models and empirical data, then apply expected value concepts to real decisions — including fair games and strategies in everyday situations.
- Dot plots, histograms, box plots, and two-way frequency tables
- Normal distribution and population percentage estimation
- Scatter plots, linear fit, and correlation coefficients
- Sample surveys, randomized experiments, and observational studies
- Conditional probability, independence, Addition Rule, Multiplication Rule
- Random variables, probability distributions, and expected value
- Permutations, combinations, and compound event probabilities